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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A reduced model for the ITER divertor based on SOLPS solutions for ITER Q = 10 baseline conditions: A. identifying options for the control parameters*

Edge codes such as SOLPS coupled to neutral codes such as EIRENE have become so comprehensive and sophisticated that they now constitute, in effect, 'code-experiments' that, as for actual experiments, can benefit from interpretation using simple models and conceptual frameworks, i.e. reduced models. The first task is the identification of options for the reduced model control parameters that are best suited for control of the action of the divertor, i.e. for control of target power loading and sputter-erosion, primarily. A strong correlation between the electron temperature at the divertor target, T e,t , and the neutral deuterium D 2 density at the target, n D2,t , flux-tube resolved, has recently been reported for a number of code studies including SOLPS-4.3 modeling of a set of ~50 ITER baseline cases: Q DT = 10, q 95 = 3, P SOL = 100 MW, metallic walls, and Ne seeding. This part A of the present study reports new results for largely the same ITER cases, confirming the strong correlations reported earlier between local values of T e,t , and (i) n D2,t , and (ii) normalized volumetric losses of power and pressure in the divertor. Strong correlations have now also been found, and are reported here for the first time, between T e,t and all of the divertor target quantities of practical interest. A physical explanation for this surprising result has not been fully identified; nevertheless it has encouraging implications for reduced modeling of the ITER divertor. For such ITER conditions, (i) the global Ne injection rate, Inj Ne [Ne/s], and (ii) the electron temperature at the location on the target where the peak power deposition occurs, T e,t @q ⊥,pk (eV), are found to be promising reduced model control parameters. In the companion report, part B, a reduced model for the ITER divertor is developed and described in detail, based on reversed-direction 2 point modelling, Rev2PM. The input to the reduced model is a value of the variable pair (T et @q ⟂,pk ,Inj Ne ) and the output are values of the various target as well as divertor-entrance quantities of practical interest, e.g. q ⊥,pk , n e,Xpt (the electron density at the poloidal location of the X-point), etc. In part B the reduced model is quantitatively characterized using one half of the code cases; it is then used to successfully predict (replicate) the code values of e.g. n e,Xpt for the other half of the cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Radiological characterization and Decommissioning of Research and Power Reactors - 15602

The production of the detailed activity and dose rate atlases (ADAs) is one of the indispensable measures in the decommissioning process of nuclear reactors which allows to determine the radiation field for optimal radiation protection as well as to quantify and characterize nuclear waste for disposal. High-detailed simulation models capable of performing neutron and radiation transport calculations at different levels of precision and details are applied for this purpose. Within the framework of the research project 'Decommissioning of Research and Power Reactors', funded by the German Federal Ministry of Education and Research (BMBF), and implemented by the Institute of Nuclear Engineering and Technology Transfer (NET) -RWTH Aachen, sophisticated simulation tools are developed. The enhances capability of these tools for the generation of the activity and dose rate distribution are tested and demonstrated on the shutdown German research reactor FRJ-2. To achieve the project goal different computational steps were required: 1. Development of a calculational CAD-based model for Monte Carlo neutron and gamma transport simulation using converter tool McCad 2. Design of the neutron source which reproduce the neutron distribution leaving the core 3. Enhancement of the simulation performance by using the hybrid deterministic Monte Carlo variance reduction methods 4. Calculation of N-flux distribution in the entire geometry 5. Development of couple codes between MCNP5 and the activation code ORIGEN2.2 This paper describes the main significant project milestones. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Development of an Outdoor Temperature Based Control Algorithm for Residential Mechanical Ventilation Control

The Incremental Ventilation Energy (IVE) model developed in this study combines the output of simple air exchange models with a limited set of housing characteristics to estimate the associated change in energy demand of homes. The IVE model was designed specifically to enable modellers to use existing databases of housing characteristics to determine the impact of ventilation policy change on a population scale. The IVE model estimates of energy change when applied to US homes with limited parameterisation are shown to be comparable to the estimates of a well-validated, complex residential energy model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

HySafe research priorities workshop report Summary of the workshop organized in cooperation with US DOE and supported by EC JRC in Washington DC November 10-11 2014.

The HySafe research priorities workshop is held on the even years between the International Conference on Hydrogen Safety (ICHS) which is held on the odd years. The research priorities workshop is intended to identify the state-of-the-art in understanding of the physical behavior of hydrogen and hydrogen systems with a focus on safety. Typical issues addressed include behavior of unintended hydrogen releases, transient combustion phenomena, effectiveness of mitigation measures, and hydrogen effects in materials. In the workshop critical knowledge gaps are identified. Areas of research and coordinated actions for the near and medium term are derived and prioritized from these knowledge gaps. The stimulated research helps pave the way for the rapid and safe deployment of hydrogen technologies on a global scale. To support the idea of delivering globally accepted research priorities for hydrogen safety the workshop is organized as an internationally open meeting. In attendance are stakeholders from the academic community (universities, national laboratories), funding agencies, and industry. The industry participation is critically important to ensure that the research priorities align with the current needs of the industry responsible for the deployment of hydrogen technologies. This report presents the results of the HySafe Research Priorities Workshop held in Washing- ton, D.C. on November 10-11, 2014. At the workshop the participants presented updates (since the previous workshop organized two years before in Berlin, Germany) of their research and development work on hydrogen safety. Following the workshop, participants were asked to provide feedback on high-priority topics for each of the research areas discussed and to rank research area categories and individual research topics within these categories. The research areas were ranked as follows (with the percentage of the vote in parenthesis): 1. Quantitative Risk Assessment (QRA) Tools (23%) 2. Reduced Model Tools (15%) 3. Indoor (13%) 4. Unintended Release-Liquid (11%) 5. Unintended Release-Gas (8%) 6. Storage (8%) 7. Integration Platforms (7%) 8. Hydrogen Safety Training (7%) 9. Materials Compatibility/Sensors (7%) 10. Applications (2%) The workshop participants ranked the need for Quantitative Risk Analysis (QRA) tools as the top priority by a large margin. QRA tools enable an informed expert to quantify the risk asso- ciated with a particular hydrogen system in a particular scenario. With appropriate verification and validation such tools will enable: * system designers to achieve a desired level of risk with suitable risk mitigation strategies, * permitting officials to determine if a particular system installation meets the desired risk level (performance based Regulations, Codes, and Standards (RCS) rather than prescrip- tive RCS), and * allow code developers to develop code language based on rigorous and validated physical models, statistics and standardized QRA methodologies. Another important research topic identified is the development of validated reduced physical models for use in the QRA tools. Improvement of the understanding and modeling of specific release phenomena, in particular liquid releases, are also highly ranked research topics. Acknowledgement The International Association HySafe, represented here by the authors, would like to thank all participants of the workshop for their valuable contributions. Particularly appreciated is the active participation of the industry representatives and the steady support by the European Com- mission's Joint Research Centre (JRC). Deep gratitude is owed for the great support by the United States Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy's Fuel Cell Technologies Office (EERE/FCTO) for the organization of the 2014 version of the hydrogen safety research priorities workshop. This page intentionally left blank.

08 HYDROGEN↗
DOE OSTI2024

Data-driven closure modeling for hypersonic turbulent flows

The Reynolds-averaged Navier–Stokes (RANS) equations remain a workhorse technology for simulating compressible fluid flows of practical interest. Due to model-form errors, however, RANS models can yield erroneous predictions that preclude their use on mission-critical problems. This report summarizes work performed from FY22-FY24 focused on improving RANS models for hypersonic flows using data-driven modeling and scientific machine learning. In this work we: 1. Investigate the current capabilities of RANS models in Sandia’s parallel aerodynamics and re-entry code (SPARC) for hypersonic flows with a focus on shock boundary layer interactions (SBLIs), 2. Assess several established corrections that exist in the literature aimed at improving predictions for SBLIs, 3. Develop improved models for the Reynolds stress tensor using tensor-basis neural networks, 4. Develop a neural-network-based variable turbulent Prandtl number model to reduce errors in wall heating in SBLIs. 5. Begin future investigations including employing the LIFE framework to improve wall heating predictions in SBLIs as well as the ensemble Kalman filter. We find that current RANS models in SPARC are deficient for complex SBLI flows. In particular, no current model jointly predicts wall heat flux, wall shear stress, and wall pressure with reasonable accuracy. Existing corrections help, but do not alleviate this issue altogether. The development of improved models for the Reynolds stress tensor via tensor-basis neural networks results in more predictive RANS models across a suite of low-speed and high-speed cases. For hypersonic boundary layers, the inclusion of the wall-normal Reynolds stress via TBNNs has an appreciable impact on the wall-normal momentum balance and wall quantities. However, we find that improvements to the Reynolds stress tensor do not address the over-prediction in wall heat flux in SBLIs. We find that a neural-network-based variable turbulent Prandtl number model systematically and substantially improves wall heating predictions for a range of SBLI cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Sustainable production of 5-hydroxymethyl furfural from glucose for process integration with high fructose corn syrup infrastructure

5-Hydroxymethyl furfural (HMF) is a platform chemical, which can be derived from lignocellulosic biomass, and used for production of liquid fuels and polymers. We demonstrate a process for production of HMF using sequential enzymatic and catalytic reactions of glucose to synthesize HMF, and simulated-moving-bed (SMB) separation to purify HMF. The adsorption thermodynamic parameters of glucose, fructose, and HMF on a commercial chromatography resin are experimentally determined for modeling the SMB-based HMF production process. The experimental data are used to develop a rigorous process model and then estimate the cost of production. Chromatographic separation of HMF has 16% lower operating costs compared to an extraction-based process and has a minimum selling price of approximately $1478 per ton. We demonstrate that the HMF process can be integrated with the high fructose corn syrup (HFCS) process, and we performed analyses considering two systems including construction of a new integrated facility and retrofitting an existing HFCS facility to produce HMF. Our analyses suggest that the latter approach is a promising short-term low-risk strategy to advance the HMF production technology to commercial scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Connecting the irreversible capacity loss in Li-ion batteries with the electronic insulating properties of solid electrolyte interphase (SEI) components.

The formation and continuous growth of a solid electrolyte interphase (SEI) layer are responsible for the irreversible capacity loss of batteries in the initial and subsequent cycles, respectively. In this article, the electron tunneling barriers from Li metal through three insulating SEI components, namely Li 2 CO 3 , LiF and Li 3 PO 4 , are computed by density function theory (DFT) approaches. Based on electron tunneling theory, it is estimated that sufficient to block electron tunneling. It is also found that the band gap decreases under tension while the work function remains the same, and thus the tunneling barrier decreases under tension and increases under compression. A new parameter, η, characterizing the average distances between anions, is proposed to unify the variation of band gap with strain under different loading conditions into a single linear function of η. An analytical model based on the tunneling results is developed to connect the irreversible capacity loss, due to the Li ions consumed in forming these SEI component layers on the surface of negative electrodes. As a result, the agreement between the model predictions and experimental results suggests that only the initial irreversible capacity loss is due to the self-limiting electron tunneling property of the SEI.

25 ENERGY STORAGE↗
DOE OSTI2013

Alternating lags of QPO harmonics: A generic model and its application to the 67 mHz QPO of GRS 1915+105

A generic model for alternating lags in quasi-periodic oscillation (QPO) harmonics is presented where variations in the photon spectrum are caused by oscillations in two parameters that characterize the spectrum. It is further assumed that variations in one of the parameters are linearly driven by variations in the other after a time delay t{sub d} . It is shown that alternating lags will be observed for a range of t{sub d} values. A phenomenological model based on this generic one is developed that can explain the amplitude and phase lag variation with energy of the fundamental and the next three harmonics of the 67 mHz QPO observed in GRS 1915+105. The phenomenological model also predicts the variation of the Bicoherence phase with energy, which can be checked by further analysis of the observational data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Modeling and Analysis of Polarization Losses in Solid Oxide Fuel Cells with Siloxane Contamination

In this study, the degradation of the solid-oxide fuel cell (SOFC) nickel-yttria stabilized zirconia anode under decamethyltetrasiloxane (L4) contamination is examined with experiments and modeling. A model is developed for the polarization losses based on the charge transfer coefficient,α, and diffusion layer thickness,δ, and fitted to the experimental data to understand how the siloxane degrades the SOFC performance with time. The results of the model indicate that the total polarization losses increase approximately 44% over the course of the 180 min experiment at 350 mA cm −2 . Activation losses dominate the polarization losses initially but decrease in their total contribution while concentration losses increase. Scanning electron microscopy (SEM) with wavelength dispersive X-ray spectroscopy (WDS) elemental mapping indicates that silicon deposition is highest at the outer edge of the anode and forms a barrier layer to fuel diffusion, increasing concentration losses. When the model is applied to other previous D4 and L4 siloxane experiments conducted over a period of 40 h, similar trends in polarization losses are observed. Polarization losses increase more rapidly with D4 compared to L4 siloxane contamination, with concentration losses increasing the fastest with both types of siloxane.

Electrochemistry↗
DOE OSTI2024

A High-Fidelity Electromagnetic Transient Model of Inverter-based Resources Integrated to an IEEE-9 Bus System for Benchmarking Studies

An inverter-based resource (IBR) is a source of electricity that is asynchronously connected to the electrical grid via an electronic power converter. These power sources lack the intrinsic behaviors of the standard power plants, presenting specific challenges to system stability. These power sources lack the intrinsic behaviors of the standards power plants and their features are almost entirely defined by the control strategy used on them, presenting specific challenges to system stability as their penetration increases into the already fragile Bulk Power System (BPS). Utilizing renewable energy has a great upside but the electrical industry needs to understand the requirements like performing electromagnetic transient (EMT) simulation studies in planning and/or in interconnection studies. This paper presents the development of a high-fidelity EMT model based on commercial equipment and field parameters, which at the same time aims to study the increasing penetration of IBRs and their impact on the actual BPS. The open-source EMT model developed will be a benchmarking example that can be used to evaluate algorithms in the power grid (including evaluating grid-forming controls, power system monitoring and operation, etc.).

Martinez Montejano, Misael↗
DOE OSTI2024

Landscape fragmentation overturns classical metapopulation thinking

Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally (“residents”) were often more resilient to fragmentation than long-ranging “migrants.” This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

WE-E-17A-02: Predictive Modeling of Outcome Following SABR for NSCLC Based On Radiomics of FDG-PET Images

Purpose: This study aims to develop predictive models of patient outcome by extracting advanced imaging features (i.e., Radiomics) from FDG-PET images. Methods: We acquired pre-treatment PET scans for 51 stage I NSCLC patients treated with SABR. We calculated 139 quantitative features from each patient PET image, including 5 morphological features, 8 statistical features, 27 texture features, and 100 features from the intensity-volume histogram. Based on the imaging features, we aim to distinguish between 2 risk groups of patients: those with regional failure or distant metastasis versus those without. We investigated 3 pattern classification algorithms: linear discriminant analysis (LDA), naive Bayes (NB), and logistic regression (LR). To avoid the curse of dimensionality, we performed feature selection by first removing redundant features and then applying sequential forward selection using the wrapper approach. To evaluate the predictive performance, we performed 10-fold cross validation with 1000 random splits of the data and calculated the area under the ROC curve (AUC). Results: Feature selection identified 2 texture features (homogeneity and/or wavelet decompositions) for NB and LR, while for LDA SUVmax and one texture feature (correlation) were identified. All 3 classifiers achieved statistically significant improvements over conventional PET imaging metrics such as tumor volume (AUC = 0.668) and SUVmax (AUC = 0.737). Overall, NB achieved the best predictive performance (AUC = 0.806). This also compares favorably with MTV using the best threshold at an SUV of 11.6 (AUC = 0.746). At a sensitivity of 80%, NB achieved 69% specificity, while SUVmax and tumor volume only had 36% and 47% specificity. Conclusion: Through a systematic analysis of advanced PET imaging features, we are able to build models with improved predictive value over conventional imaging metrics. If validated in a large independent cohort, the proposed techniques could potentially aid in identifying patients who might benefit from adjuvant therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Investigation of particle–wall interaction in a pseudo-2D fluidized bed using CFD-DEM simulations

Here, we report on discrete element method simulations of a pseudo-two-dimensional (pseudo-2D) fluidized bed to investigate particle–wall interactions. Detailed information on macroscopic flow field variables, including solids pressure, granular temperature, and normal and tangential wall stresses are analyzed. The normal wall stress differs from the solids pressure because of the strong anisotropic flow behavior in the pseudo-2D system. A simple linear relationship exists between normal wall stress and solids pressure. In addition, an effective friction coefficient can be derived to characterize particle–wall flow interaction after evaluating the normal and tangential wall stresses. The effects of inter-particle and particle–wall friction coefficients are evaluated. Strong anisotropic flow behavior in the pseudo-2D system needs to be considered to validate the two-fluid model where the boundary condition is usually developed based on an isotropic assumption. The conclusion has been confirmed by simulation with different particle stiffnesses. Assumptions in the newly developed model for 2D simulation are further examined against the discrete element method simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Thermodynamic Modeling of Heat Engines Including Heat Transfer and Compression–Expansion Irreversibilities

In this paper, a thermodynamic model based on an endoreversible engine approach is developed to analyze the performance of heat engines operating under different thermodynamic cycles. The model considers finite heat transfer rate, variable heat source and sink temperatures, and irreversibilities associated with the expansion and compression. Expressions for the maximum power and efficiency at maximum power output are obtained as a function of hot and cold reservoir temperatures, the equivalent isentropic efficiency of compression and expansion components, and the effective conductance ratio between heat exchangers. In all cases, the Curzon–Ahlborn efficiency is retrieved at constant reservoir temperatures and neglected compression–expansion irreversibilities. The proposed model allows assessing the effect of isentropic efficiencies and heat exchanger design and operation characteristics for different thermodynamic cycles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Quantification of Uncertainty in Extreme Scale Computations (QUEST)

QUEST was a SciDAC Institute comprising Sandia National Laboratories, Los Alamos National Laboratory, the University of Southern California, the Massachusetts Institute of Technology, the University of Texas at Austin, and Duke University. The mission of QUEST is to: (1) develop a broad class of uncertainty quantification (UQ) methods/tools, and (2) provide UQ expertise and software to other SciDAC projects, thereby enabling/guiding their UQ activities. The USC effort centered on the development of reduced models and efficient algorithms for implementing various components of the UQ pipeline. USC personnel were responsible for the development of adaptive bases, adaptive quadrature, and reduced models to be used in estimation and inference.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Hybrid Cyber-attack Detection in Photovoltaic Farms

Here, to address the cyber-physical security in PV farms, a hybrid cyber-attack detection is proposed in this manuscript. To secure PV farms, the proposed method integrates model-based and data-driven methods by fusing the detection score at the device and system levels. First, a model-based cyber-attack detection method is developed for each PV inverter. A residual between the estimation of the Kalman filter and measurement is calculated. By leveraging the calculated residual from all inverters, a squared Mahalanobis distance is developed for device detection score generation. At the system level, a convolutional neural network (CNN) is proposed to detect cyber-attack using the waveform data at the point of common coupling (PCC) in PV farms. To improve the CNN detection accuracy, a set of well-designed features are extracted from the raw waveform data. Finally, a weighted detection score fusion method is proposed to combine device and system detection scores by using their complementary strength. The feasibility and robustness of the proposed method are validated by testing cases and a comparative experiment.

14 SOLAR ENERGY↗
DOE OSTI2018

Model-Based Air Flow Path Optimization of Heat Pump Clothes Dryer

A heat pump clothes dryer (HPCD) uses a vapor compression system to dry clothes. The condenser heats air, which passes through the drum to evaporate moisture out of the clothes, and the evaporator condenses water out of the air stream. As a result, the HPCD can achieve 50% energy savings compared to a conventional electric resistance dryer. In this work we developed a physics-based, quasi-steady-state HPCD system model with detailed heat exchanger and compressor models. The system model can simulate the inherently transient HPCD drying process, to size components, and to reveal trends in key variables (e.g. compressor discharge temperature, power consumption, required drying time, etc.) The system model was calibrated using experimental data from a prototype HPCD. Air leakages, in and out, along the closed air circulation path of HPCD cause varied effects on the performance. Understanding the location, magnitude, and direction of air leakage of the heat pump clothes dryer is critical for accurately characterizing the performance and developing a high-performance design. The system model was used to reveal the impacts. In addition, model-based parametric optimizations were conducted to design the HPCD charge inventory, flow rate, air path and leak points for optimum performance.

Shen, Bo↗
DOE OSTI2021

The interpenetration polymer network in a cement paste–waterborne epoxy system

The formation of the interpenetrating polymer network (IPN) structure within the cement-polymer system has been revealed by experiments from 2 dimensional to 3-dimensional scales. However, the microstructure design and performance prediction of IPN as a function of specific C-S-H/polymer components or ingredients' parameters e.g. water to cement ratios (w/c), polymer to cement ratios (p/c), monomer components, degree of polymerization (DP), etc. is by far not available. Here we developed a mesoscale model for IPN visualization based on the Flory-Huggins interaction theory which was applied to cement science for the first time. All the ingredients in the micro-structure were considered as soluble beads with rational sizes based on their properties obtained by molecular dynamic methods. The interaction parameters of each bead were then determined based on their element ratios and chemical backbones. The model was validated with the waterborne epoxy-cement material (WECM) in which a novel waterborne epoxy resin (WEP) was prepared and impregnated. The verification results on the 2D-3D scale show that the developed model predicts the WECM's IPN structures by rule and line concerning DP, w/c, and p/c in the mixture. The C-S-H beads were progressively scaled in size which alters the C-S-H texture to have completely different dissolution characteristics. Beads of diameter ~6 Å are more unstable and soluble which enable them to form a continuous phase in water or a composite structure with WEP. In contrast, beads with diameters larger than 10 Å have different properties with stronger nucleation effects. The results also suggest the impregnation content of WEP in cement-based material should be limited to 10% vol. to prevent the polymer IPN from decomposing into discrete clusters. The application of Flory-Huggins theory in cement-based composites demonstrates great potential in performance prediction and microstructure design.

36 MATERIALS SCIENCE↗