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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Data requirements for improving the Quantitative Risk Assessment of liquid hydrogen storage systems

Quantitative Risk Assessment (QRA) supports the development of risk-informed safety codes and standards which are employed to enable the safe deployment of hydrogen technologies essential to decarbonize the transportation sector. System reliability data is a necessary input for rigorous QRA. Here, the lack of reliability data for bulk liquid hydrogen (LH 2 ) storage systems located on site at fueling stations limits the use of QRAs. In turn, this hinders the ability to develop the necessary safety codes and standards that enable worldwide deployment of these stations. Through a QRA-based analysis of a LH 2 storage system, this work focuses on identifying relevant scenario and probability data currently available and ascertaining future data collection requirements regarding risks specific to liquid hydrogen releases. The work developed consists of the analysis of a general bulk LH 2 storage system design located at a hydrogen fueling station. Failure Mode and Effect Analysis (FMEA) and traditional QRA modeling tools such as Event Sequence Diagrams (ESD) and Fault Tree Analysis (FTA) are employed to identify, rank, and model risk scenarios related to the release of LH 2 . Based on this analysis, scenario and reliability data needs to add LH 2 -related components to QRA are identified with the purpose of improving the future safety and risk assessment of these systems.

08 HYDROGEN↗
DOE OSTI2020

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Hermeticity of SiC/SiC composite and monolithic SiC tubes irradiated under radial high-heat flux

Demonstration of hermetic SiC fiber–reinforced SiC matrix composite cladding under normal operating environments has been identified as one of the most critical feasibility issues for accident-tolerant fuel cladding in light-water reactors. This study provides critical experimental data needed for understanding the effects of irradiation on hermeticity. SiC composite and monolithic tubes were neutron-irradiated to 2 displacements per atom with and without a nominal radial heat flux of 0.6 MW/m2 to produce a simulated in-pile stress state for the normal operation of a light-water reactor. The through-thickness temperature gradient under irradiation results in a gradient in swelling, which causes a significant stress buildup. Such irradiation-induced stress was modeled using a commercial finite element analysis code. The radial heat flux–irradiation synergism was experimentally investigated by constructing a special irradiation capsule and evaluating the helium hermeticity of the specimens. The simulated stress state exhibited a near equi-biaxial tensile axial and hoop stress of ~150 MPa at the inner surface of the SiC composite tube. This stress level is potentially beyond the matrix cracking stress. Degradation of hermeticity of the SiC composite tubes was observed after irradiation, indicating irradiation-induced cracking, whereas the irradiated monolithic SiC tubes remained hermetic. In conclusion, the results indicate that loss of hermeticity caused by radiation-induced microcracking is a potential issue for SiC composite cladding, depending on the magnitude of the temperature gradients. Coating the outer surface of the cladding was identified as a mitigation strategy that might overcome the cracking issue.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Off-line commissioning of the St. Benedict radiofrequency quadrupole cooler-buncher

The St. Benedict ion trapping system, which aims to measure the β - v angular correlation parameter in superallowed-mixed mirror transitions, is under construction at the University of Notre Dame. These measurements will provide much-needed data to improve the accuracy of the V ud element of the CKM matrix. One of the major components of this system is the radio frequency quadrupole cooler-buncher, which is necessary to create low-emittance ion bunches for injection into the measurement Paul trap. The off-line commissioning of the cooler-buncher, using a potassium ion source, determined that the device could produce cooled ion bunches characterized by a 50-ns full-width-half-maximum time width at its exit. The commissioning results also determined the trapping efficiency to be 93(1)% and the trapping half-life to be 20.0(5) s.

Paul trap↗
DOE OSTI2020

Single-phase, natural circulation annular flow measurements for cartridge loop irradiation experiments

The nuclear industry is increasingly considering cartridge-style experiments for irradiation testing of advanced reactor fuels and materials under flowing conditions. Cartridge loops do not require the extensive support infrastructure that are necessary for external flow loops and minimize the possibility of coolant solidification over the long distance from the reactor to the external facilities. However, there is a general lack of quality flow data for internally heated fluids in an annular configuration representative of a cartridge-type irradiation experiment, particularly one with natural circulation. To address this data need, a series of experiments was conducted to measure the natural circulation flow rates of pressurized water in a sealed, internally heated vessel with annular flow conditions that represent a molten salt or sodium cartridge loop. Temperatures and flow rates were measured under steady-state and transient conditions. Here, this paper describes the facility, methods, and results of the experiments, including the determination of nondimensional parameters. A simple 1D model of the natural convection flow rates agrees well with the experimental results. Applying this model to simulate a liquid salt cartridge experiment predicts that natural circulation flow might be able to provide liquid salt Reynolds numbers similar to those of some molten salt reactor concepts at relevant power densities.

42 ENGINEERING↗
DOE OSTI2023

Reactivity-initiated accidents in two pressurized water reactor high burnup core designs

Here, this paper presents a safety analysis of two proposed core loadings for 24-month Pressurized Water Reactor (PWR) fuel cycles. This analysis focuses on reactivity-initiated accidents (RIAs) and evaluates core safety performance impacts of rod-averaged burnup limits up to 75 GWD/MTU and less than 7 % enriched UO 2 . The capabilities of Polaris, PARCS, and RELAP5-3D are leveraged to evaluate the core neutronic and thermal–hydraulic behavior for normal-operation, uncontrolled control rod withdrawal (CRW) transients, and control rod ejection (CRE) accidents. The two core designs are compared to identify features of realistic high burnup/extended enrichment core design approaches which have significant safety impact, identify experimental data needs for high-fidelity predictive modeling, and provide recommendations for future high burnup core designs. The first core design evaluated in this study was developed by Southern Nuclear Company and used an ZrB 2 Integral Fuel Burnable Absorber (IFBA) and B 4 C Wet-Annular Burnable Absorber (WABA)-based burnable poison strategy. The second core design assessed in this work used a Gd 2 O 3 -doped UO 2 burnable poison, similar to that used in boiling water reactors or French PWRs. Results indicate that fuel thermal limits are maintained for limiting CRW and hot full power (HFP) CRE transients. Cladding failure is predicted for the highest energy deposition rods in each core during limiting hot zero power (HZP) CRE accidents (where maximum radially averaged enthalpy exceeds 120 cal/g), though licensing may be permissible with a limited number of failed rods. While concerns exist regarding high critical boron concentration during steady state for the IFBA core and large plenum pressures for the gadolinia core design, the analysis demonstrates adequate safety performance during limiting RIA accident scenarios for two representative high burnup core designs. Design changes limiting plenum pressures and implementation of accident tolerant fuel (ATF) cladding features which minimize hydriding and susceptibility to pellet-cladding mechanical interaction (PCMI) are recommended for future high burnup fuel concepts. To support the technical basis for burnup limit increases, high-fidelity fuel performance models are needed to address physical effects not considered in this analysis, and high burnup irradiated fuel tests are required to extend applicability of the fuel failure limits and validate existing and future models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Development and demonstration of a BISON–Griffin modeling framework for the design of targeted TRISO transient experiments in the Transient Reactor Test Facility

Uranium oxycarbide (UCO)-bearing tri-structural isotropic (TRISO) particle fuels are expected to be used in numerous U.S. commercial reactor applications within the next decade. Here, in this work, we reviewed historical particle fuel transient experiments to identify gaps in TRISO fuel performance transient testing. A BISON–Griffin modeling framework was then developed to conduct preliminary TRISO transient analyses and begin to address these gaps. The framework was demonstrated using limiting-case transient conditions from a prototypic high-temperature gas-cooled reactor (HTGR). It was then applied to develop a matrix of experiments that could be performed in the Transient Reactor Test Facility (TREAT) to (1) evaluate UCO-fueled particle performance at moderate and high heat rates, (2) assess whether historical testing involving UO 2 -fueled particles is applicable to modern UCO-fueled particles, (3) deconvolute the impacts of temperature and heat rate on particle transient response, and (4) collect the data needed for fuel performance model validation and/or further development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

The persistent nonperturbative charm enigma

The question of the existence and possible magnitude of nonperturbative (often called “intrinsic”) charm in the proton has long confounded attempts to cleanly isolate such a contribution in global analyses of high-energy experiments. In this letter, we show that the available (non)perturbative QCD theory and hadronic data have still not developed to a sufficient level to clearly resolve this problem. We highlight a number of challenging aspects that must be confronted in extracting nonperturbative charm in PDF fits, and in so doing, present an updated next-to-next-to-leading order CT analysis of fitted charm, CT18 FC, which we also compare to recent studies. We outline the theory developments and future data needed to make progress on this subject.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Integration of ecosystem science into radioecology: A consensus perspective

In the Fall of 2016 a workshop was held which brought together over 50 scientists from the ecological and radiological fields to discuss feasibility and challenges of reintegrating ecosystem science into radioecology. There is a growing desire to incorporate attributes of ecosystem science into radiological risk assessment and radioecological research more generally, fueled by recent advances in quantification of emergent ecosystem attributes and the desire to accurately reflect impacts of radiological stressors upon ecosystem function. This work is a synthesis of the discussions and consensus of the workshop participant's responses to three primary questions, which were: 1) How can ecosystem science support radiological risk assessment? 2) What ecosystem level endpoints potentially could be used for radiological risk assessment? and 3) What inference strategies and associated methods would be most appropriate to assess the effects of radionuclides on ecosystem structure and function? The consensus of the participants was that ecosystem science can and should support radiological risk assessment through the incorporation of quantitative metrics that reflect ecosystem functions which are sensitive to radiological contaminants. The participants also agreed that many such endpoints exit or are thought to exit and while many are used in ecological risk assessment currently, additional data need to be collected that link the causal mechanisms of radiological exposure to these endpoints. Finally, the participants agreed that radiological risk assessments must be designed and informed by rigorous statistical frameworks capable of revealing the causal inference tying radiological exposure to the endpoints selected for measurement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Inelastic Triatom-Atom Quantum Close-Coupling Dynamics in Full Dimensionality: All Rovibrational Mode Quenching of Water Due to the H Impact on a Six-Dimensional Potential Energy Surface

The rovibrational level populations, and subsequent emission in various astrophysical environments, are driven by inelastic collision processes. The available rovibrational rate coefficients for water have been calculated using a number of approximations. We present a numerically exact calculation for the rovibrational quenching for all water vibrational modes due to collisions with atomic hydrogen. The scattering theory implements a quantum close-coupling (CC) method on a high level ab initio six-dimensional (6D) potential energy surface (PES). Total rovibrational quenching cross sections for excited bending levels were compared with earlier results on a 4D PES with the rigid-bender closecoupling (RBCC) approximation. General agreement between 6D-CC and 4DRBCC calculations are found, but differences are evident including the energy and amplitude of low-energy orbiting resonances. Quenching cross sections from the symmetric and asymmetric stretch modes are provided for the first time. The current 6D-CC calculation provides accurate inelastic data needed for astrophysical modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Geophysical Monitoring Shows that Spatial Heterogeneity in Thermohydrological Dynamics Reshapes a Transitional Permafrost System

Climate change is causing rapid changes of Arctic ecosystems. Yet, data needed to unravel complex subsurface processes are very rare. Using geophysical and in-situ sensing, this study closes an observational gap associated with thermohydrological dynamics in discontinuous permafrost systems. It highlights the impact of vegetation and snow thickness distribution on subsurface thermohydrological properties and processes. Large snow accumulation near tall shrubs insulates the ground and allows for rapid and downward heat flow. Thinner snowpack above graminoid results in surficial freezing and prevents water from infiltrating into the subsurface. Analyzing short term disturbances, we found that lateral flow could be a driving factor in talik formation. Inter-annual measurements show that deep permafrost temperatures increased by about 0.2°C over two years. The results, which suggest that snow-vegetation-subsurface processes are tightly coupled, will be useful for improving predictions of Arctic feedback to climate change, including how subsurface thermohydrology influences CO 2 and CH 4 fluxes.

58 GEOSCIENCES↗
DOE OSTI2025

Accurate Dehydrogenation Enthalpies Dataset for Liquid Organic Hydrogen Carriers

This contribution presents a comprehensive extension of the QM9 dataset (originally at 133 K molecules) with the calculation of G4MP2 enthalpies for 9,841 molecules, featuring up to nine heavy atoms. We present QM9-LOHC, a (de)hydrogenation dataset of 10,373 reactions, including a minimum of 5.5% weight hydrogen storage capacity in line with the Department of Energy standards for Liquid Organic Hydrogen Carriers (LOHC). By utilizing the accurate quantum chemical method G4MP2 we expand the QM9 database and explore new avenues for the exploration of hydrogen storage technologies (electrochemical LOHCs, alkali metal-LOHCs, and mixtures of LOHCs). The QM9-LOHC dataset, with its focus on reactions that vary only by hydrogen saturation levels, provides a needed data resource for advancing the design and optimization of both conventional and innovative LOHC systems, and high-fidelity data for molecular discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Supervised learning and the finite-temperature string method for computing committor functions and reaction rates

A central object in the computational studies of rare events is the committor function. Though costly to compute, the committor function encodes complete mechanistic information of the processes involving rare events, including reaction rates and transition-state ensembles. Under the framework of transition path theory, Rotskoff et al. [Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, Proceedings of Machine Learning Research (PLMR, 2022), Vol. 145, pp. 757–780] proposes an algorithm where a feedback loop couples a neural network that models the committor function with importance sampling, mainly umbrella sampling, which collects data needed for adaptive training. Here, in this work, we show additional modifications are needed to improve the accuracy of the algorithm. The first modification adds elements of supervised learning, which allows the neural network to improve its prediction by fitting to sample-mean estimates of committor values obtained from short molecular dynamics trajectories. The second modification replaces the committor-based umbrella sampling with the finite-temperature string (FTS) method, which enables homogeneous sampling in regions where transition pathways are located. We test our modifications on low-dimensional systems with non-convex potential energy where reference solutions can be found via analytical or finite element methods, and show how combining supervised learning and the FTS method yields accurate computation of committor functions and reaction rates. We also provide an error analysis for algorithms that use the FTS method, using which reaction rates can be accurately estimated during training with a small number of samples. The methods are then applied to a molecular system in which no reference solution is known, where accurate computations of committor functions and reaction rates can still be obtained.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Heavy ion beam probe for Wendelstein 7-X measurement capabilities as projected through its design

A heavy ion beam probe (HIBP) diagnostic is being developed for studies of plasma equilibrium and turbulence in the optimized Wendelstein 7-X (W7-X) stellarator. Operation of W7-X has experimentally demonstrated that its optimized magnetic field results in improved neoclassical particle confinement and, as a result, turbulence is the predominant cause of energy transport. The HIBP will have the unique ability to provide experimental data needed to complement models of both neoclassical and turbulent transport. It will acquire direct measurements in the W7-X plasma interior of the electric potential (needed for understanding ambipolar particle flux) and fluctuations of electron density and potential (needed for understanding turbulence). The HIBP for W7-X will inject singly charged ion beams with energies of up to 2 MeV and is designed to access the upper cross section of the W7-X plasma. We use trajectory simulations to illustrate the plasma coverage that the diagnostic can achieve in the reference magnetic configurations of W7-X. We calculate beam signal levels, discuss anticipated measurement sensitivity of broadband fluctuations of electron density and plasma potential, and show how they depend on plasma density. We also discuss the diagnostic sensitivity to equilibrium plasma potential.

Instruments & Instrumentation↗
DOE OSTI2025

Implementation of the D1S Methodology for Shutdown Dose Rate Calculations in the OpenMC Monte Carlo Particle Transport Code

We present an implementation of the direct one-step (D1S) methodology for shutdown dose rate (SDR) calculations in the OpenMC Monte Carlo particle transport code. In addition to being the first fully open-source D1S implementation, it is also the first to require no ad hoc source code or nuclear data library modifications. The code can seamlessly switch between production of prompt and decay photons based on a user input parameter, and the decay data needed for decay photon generation are made available through a depletion chain file, which is already used for OpenMC’s built-in depletion/activation solver. A set of Python functions significantly eases the burden of computing and applying time correction factors needed to properly account for the time dependence of radionuclide activity. To assess the accuracy of the D1S implementation, SDR calculations have been carried out for three problems: a prism of iron irradiated by 14-MeV neutrons, the ITER port plug computational benchmark, and the Frascati Neutron Generator (FNG) ITER dose rate benchmark problem from the Shielding INtegral Benchmark Archive and Database (SINBAD). For each of these problems, comparisons were made to calculations using the rigorous two-step (R2S) method. The results on the iron prism problem illustrate how the D1S method achieves superior spatial resolution compared to the R2S method without the need for spatial discretization of the activation regions. The D1S and R2S results for the ITER port plug benchmark agree well with previously reported results in the literature. While the D1S results are 10% to 15% lower than the R2S results, this may be due to stochastic uncertainty and/or spatial discretization in the R2S calculations. On the FNG dose rate benchmark problem, the D1S method produces dose rate estimates that are within 4% of the dose rates predicted using a cell-based R2S workflow. The D1S estimates of the SDR are also in reasonable agreement with the experimental measurements and show the same basic trends that have been observed in previous works. A qualitative analysis of the execution time and uncertainty for the R2S and D1S workflows suggests that the D1S method would attain a higher figure of merit.

D1S method↗
DOE OSTI2023

Simulation-based analysis of different curb space type allocations on curb performance

Curbspace is a limited resource in urban areas. Delivery, ridehailing and passenger vehicles must compete for spaces at the curb. Cities are increasingly adjusting curb rules and allocating curb spaces for uses other than short-term paid parking, yet they lack the tools or data needed to make informed decisions. In this research, we analyze and quantify the impacts of different curb use allocations on curb performance through simulation, covering various mixes of curbspace uses (bus stops, paid parking, passenger pick-up/drop-off zones, and commercial vehicle loading zones), parking rules, and driver rule compliance. Three metrics (including two new ones) are developed to evaluate the performance of the curb, covering productivity and accessibility of passengers and goods, and CO 2 emissions. The metrics are calculated for each scenario across a wide range of input parameters (traffic volume, parking demand rate, vehicle dwell time, and street design speed) and compared to each other and to a baseline scenario. This work can inform policy decisions by providing municipalities a tool to analyze various curb management strategies and choose the ones that produce results more in line with their policy goals.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

The Sensitivity of Variational Bayesian Neural Network Performance to Hyperparameters

In scientific applications, predictive modeling is often of limited use without accurate uncertainty quantification (UQ) to indicate when a model may be extrapolating or when more data needs to be collected. Bayesian Neural Networks (BNNs) produce predictive uncertainty by propagating uncertainty in neural network (NN) weights and offer the promise of obtaining not only an accurate predictive model but also accurate UQ. However, in practice, obtaining accurate UQ with BNNs is difficult due in part to the approximations used for model training (such as those made in variational inference) and in part to the need to choose a suitable set of hyperparameters; these hyperparameters outnumber those needed for traditional NNs and often have opaque effects on the results. We aim to shed light on the effects of hyperparameter choices for variational BNNs by performing a global sensitivity analysis of variational BNN performance under varying hyperparameter settings. Our results indicate that many of the hyperparameters interact with each other to affect both predictive accuracy and UQ. For improved usage of variational BNNs in real-world applications, we suggest that thorough hyperparameter tuning, including tuning of prior hyperparameters and loss function parameters, is essential for accurate UQ in variational BNNs.

97 MATHEMATICS AND COMPUTING↗