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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 OSTI2022

Eucalyptus grandis $\mathrm{AUX/INDOLE}$-3-$\mathrm{ACETIC}$ $\mathrm{ACID}$ 13 (EgrIAA13) is a novel transcriptional regulator of xylogenesis

Auxin is a crucial phytohormone regulating multiple aspects of plant growth and differentiation, including regulation of vascular cambium activity, xylogenesis and its responsiveness towards gravitropic stress. Although the regulation of these biological processes greatly depends on auxin and regulators of the auxin signalling pathway, many of their specific functions remain unclear. Therefore, the present study aims to functionally characterise Eucalyptus grandis AUX/INDOLE-3-ACETIC ACID 13 (EgrIAA13), a member of the auxin signalling pathway. In Eucalyptus and Populus, EgrIAA13 and its orthologs are preferentially expressed in the xylogenic tissues and downregulated in tension wood. Therefore, to further investigate EgrIAA13 and its function during xylogenesis, we conducted subcellular localisation and Induced Somatic Sector Analysis experiments using overexpression and RNAi knockdown constructs of EgrIAA13 to create transgenic tissue sectors on growing stems of Eucalyptus and Populus. Since Aux/IAAs interact with Auxin Responsive Factors (ARFs), in silico predictions of IAA13-ARF interactions were explored and experimentally validated via yeast-2-hybrid experiments. Our results demonstrate that EgrIAA13 localises to the nucleus and that downregulation of EgrIAA13 impedes Eucalyptus xylem fibre and vessel development. We also observed that EgrIAA13 interacts with Eucalyptus ARF2, ARF5, ARF6 and ARF19A. Based on these results, we conclude that EgrIAA13 is a regulator of Eucalyptus xylogenesis and postulate that the observed phenotypes are likely to result from alterations in the auxin-responsive transcriptome via IAA13-ARF modules such as EgrIAA13-EgrARF5. Our results provide the first insights into the regulatory role of EgrIAA13 during xylogenesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Time-Dependent 600 °C Post-Weld Heat Treatment Response of Laser-Wire-Directed Energy Deposited Austenitic Stainless Steel Claddings on Carbon Steel

Austenitic stainless steel overlay claddings are often used to protect nuclear reactor pressure vessels from corrosion. Arc welding processes are traditionally employed, which require a high heat input to bond the dissimilar metals, creating a large heat-affected zone and high residual stress that demands a lengthy stress-relieving post-weld heat treatment, up to 48 hours. High energy beam (e.g., laser, electron beam) directed energy deposition-based overlay cladding processes show promise for fabricating claddings with superior performance compared to arc welded ones because of their localized heat input; however, their necessity and time of post-weld heat treatment are currently unclear. In this research, we investigate the time dependence of a 600 C stress-relieving post-weld heat treatment of austenitic stainless steel clad on low carbon steel by laser-wire-directed energy deposition, comparing the microstructure and mechanical properties of the as-fabricated condition to 2-, 10-, and 48-hour heat treatment times. Diffusion simulations and microscopy show a gradual carburization of the stainless steel cladding and decarburization of the heat-affected zone/base metal. Nanoindentation testing shows up to a 1.8–2.69 embrittlement in the cladding and a 0.33 to 0.69 softening in the heat-affected zone after the 48-hour post-weld heat treatment. Tensile testing of the cladding composites reveals that increasing post-weld heat treatment time raises clad cracking susceptibility due to intergranular carbide formation and shows that laser-wire-directed energy deposition claddings may not require post-weld heat treatment.

Coating↗
DOE OSTI2024

Hot-Roll Fabrication of Anisotropic Nanograin Nd-Fe-B Magnet

Nd-Fe-B based magnets have the highest energy product among all permanent magnets, which is required for numerous clean energy technologies. For higher temperature applications (T > 150°C), additions of heavy rare earth elements (HREEs) such as Dy are required to maintain sufficient coercivity during operation. Additions of Dy are expensive. Thus, it is desirable to reduce the need for HREEs by reducing the grain size to the nanoscale, which increases the coercivity and decreases its temperature dependence. Here, we report a novel nanograin Nd-Fe-B magnet fabrication method that is continuous and inexpensive. The process uses mechanically milled Nd-Fe-B melt-spun flakes as feedstock powder that is packed into a metal vessel and then hot rolled to form a fully dense and highly textured strip magnet with tailored thicknesses, down to 800 µm. Finally, using this process, fully dense nanograin bulk magnets can be synthesized in minutes compared to the traditional multi-step processes that are typically low throughput.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Overview of recent progress in 3D field physics in KSTAR

Various 3D field physics challenges of magnetically confined plasmas arise when the driving source comes from either externally applied non-axisymmetric 3D magnetic perturbations or plasma instabilities inside the plasma. Recently, several key outstanding topics of 3D field physics have been extensively studied in the Korean Superconducting Tokamak Advanced Research (KSTAR), such as edge-localized-mode (ELM) control by resonant magnetic perturbation (RMP), error field (EF) control, 3D field effects on rotation and transport, and RMP-induced alteration of divertor heat flux and detachment. KSTAR has a few physically unique features (i.e., high rotation and long-pulse plasmas with a low intrinsic EF) and machine/diagnostic capabilities (i.e., 3-row in-vessel control coil and state-of-the-art 2D/3D imaging diagnostics), which have been taken advantage of until now to address critical 3D field physics issues relevant to ITER and K-DEMO. Among many remarkable achievements are the robust access to and control of n = 1 RMP ELM suppression, along with a development of its physics basis tools, parameter expansion, optimization, and long-pulse control techniques. Nonetheless, a series of unresolved 3D physics themes, as well as limited coverage of 3D field operating regimes, have also been identified as future works for the 3D field research in KSTAR. In this paper, we provide an overview about the recent progress of KSTAR 3D field physics and present future plans of KSTAR 3D research toward a future fusion reactor.

3D field physics↗
DOE OSTI2020

Radiation Effects in Concrete for Nuclear Systems

Concrete is massively used in the construction of critical safety-related components in nuclear power plants. Among those, the concrete biological shield is exposed to high levels of neutron and gamma irradiation exiting the reactor pressure vessel. This article provides a comprehensive overview of the state-of-the-art knowledge on irradiated concrete. First, the fundamental irradiation-induced degradation mechanisms occurring at the level of the concrete constituents such as rock-forming minerals and hydrated cementitious phases are examined. The critical role of the mineralogical and chemical composition regarding concrete resistance against radiation effects such as amorphization, irradiation-induced expansion and radiolytic gas release are detailed. Second, the interactions between the varied irradiated phases are comprehensively analyzed and put in perspectives with the effects of prolonged irradiation on the structural properties of concrete aggregates, cement paste, and concretes. Finally, the significance of irradiation for the long-term operation of nuclear power plants is discussed in the light of the most recent knowledge and its limitations.

Le Pape, Yann↗
DOE OSTI2021

Magnetic-Confinement Fusion—Plasma Theory: Tokamak Magnetohydrodynamic Equilibrium and Stability

Magnetohydrodynamics (MHD) provides a useful model to describe the crucial plasma macroscopic equilibrium and stability behaviors in toroidal tokamak devices by considering the plasma as a conducting fluid interacting with a surrounding confining electromagnetic field. MHD is the most basic plasma model, incorporating most large-scale phenomena, including plasma equilibrium and all major instabilities. MHD equations are obtained by taking moments of the Boltzmann equations for different plasma species. They provide a set of comprehensive physics constrains to compute and optimize the equilibrium plasma shape and pressure and current profiles that are critical to its stability and performance. In the ideal case, the equations have special properties that lead to efficient numerical calculation schemes, the most important of which is the ideal MHD energy principle for linear stability against small departures from equilibrium. In a tokamak plasma, equilibrium pressure is mostly destabilizing for MHD modes, whereas equilibrium current is also often a major driving force. Plasma resistivity creates new freedom for a MHD instability to grow, but there are also cases where the plasma resistivity plays a stabilizing role. Equilibrium toroidal flow and/or flow shear can affect MHD instabilities. Principal MHD instabilities include the internal kink mode, sawtooth, fishbone, external kink, resistive wall mode, resistive interchange, tearing and neoclassical tearing modes (NTMs), locked modes, toroidal Alfven eigenmodes (TAEs), and edge localized modes (ELMs). Fast-growing MHD instabilities can lead to an abrupt plasma disruption and termination that can potentially damage the device plasma facing components (PFCs) and in-vessel structures. Furthermore, an important MHD application is to develop robust techniques to mitigate and control MHD instabilities.

Dispersive pellet injection↗
DOE OSTI2022

Origin, parameters, and underlying deformation mechanisms of propagating deformation bands in irradiated 316L stainless steel

Lüders-type propagating deformation bands were observed in specimens of irradiated 316L stainless steel samples removed from Spallation Neutron Source target vessels after service. Mechanical testing with digital image correlation (DIC) and in-situ tensile testing with scanning electron microscopy electron backscatter diffraction showed that the observed Lüders-type behavior was not related to the known transformation-induced plasticity or twinning-induced plasticity behavior. Instead, the phenomenon occurs at small local strain values before a significant amount of martensite or deformation twins appear in the microstructure. Microstructural analysis and in-situ mechanical test results suggest Lüders-type band formation and propagation were related to the appearance and evolution of defect-free channels—analogous to slip bands. A modified Swift equation with a Ludwigson-like component was offered to rationalize the phenomenon and model the strain-softening processes at small strain values. Finally, the results indicate complex microstructural processes and deformation mechanisms were active at small strain values and underline the benefits of advanced mechanical test approaches such as DIC.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Tungsten disulfide nanotubes enhance flow-induced crystallization and radio-opacity of polylactide without adversely affecting in vitro toxicity

Treatment of vascular disease, from peripheral ischemia to coronary heart disease (CHD), is poised for transformation with the introduction of transient implants designed to “scaffold” regeneration of blood vessels and ultimately leave nothing behind. Improved materials could expand the use of these devices. Here, we examine one of the leading polymers for bioresorbable scaffolds (BRS), polylactide (PLA), as the matrix of nanocomposites with tungsten disulfide (WS 2 ) nanotubes (WSNT), which may provide mechanical reinforcement and enhance radio-opacity. We evaluate in vitro cytotoxicity using vascular cells, flow-induced crystallization and radio-opacity of PLA-WSNT nanocomposites at low WSNT concentration. A small amount of WSNT (0.1 wt%) can effectively promote oriented crystallization of PLA without compromising molecular weight. And radio-opacity improves significantly: as little as 0.5 to 1 wt% WSNT doubles the radio-opacity of PLA-WSNT relative to PLA at 17 keV. The results suggest that a single component, WSNT, has the potential to increase the strength of BRS to enable thinner devices and increase radio-opacity to improve intraoperative visualization. Here, the in vitro toxicity results indicate that PLA-WSNT nanocomposites are worthy of investigation in vivo. Although substantial further preclinical studies are needed, PLA-WSNT nanocomposites may provide a complement of material properties that may improve BRS and expand the range of lesions that can be treated using transient implants.

36 MATERIALS SCIENCE↗
DOE OSTI2020

I 2 S-LWR microchannel heat exchanger design and experimental validation

The Integral Inherently Safe Light Water Reactor (I 2 S-LWR) includes primary-to-secondary coolant heat exchangers located in the downcomer of the reactor pressure vessel. A microchannel heat exchanger (MCHX) configuration is selected to meet the limited available volume and high heat duty requirements. The design, modeling, and optimization of the liquid-liquid MCHX is outlined. In addition, the performance of a MCHX test section representative of the I 2 S-LWR MCHX design is validated experimentally. Experimental results show that heat transfer and pressure drop correlations developed for larger, macroscale channels lead to accurate predictions of performance. Additionally, this study shows that an MCHX can deliver the required heat duties within the available space and pressure drop constraints of the overall I2 S-LWR design.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Improved natural convection heat transfer correlations for reactor cavity cooling systems of high-temperature gas-cooled reactors: From computational fluid dynamics to Pronghorn

The Reactor Cavity Cooling System (RCCS) is a common reactor safety system in High Temperature Gas Cooled Reactors (HTGR) that removes heat from the Reactor Pressure Vessel (RPV) by radiation ($\sim 80\%$) and natural convection ($\sim 20\%$). For simulation of accident scenarios of HTGRs, intermediate fidelity and system codes models must be employed for limiting the models' execution time. While accurate quantification of the radiative heat transfer is available in these models, quantification of natural convection must rely on correlations of questionable accuracy for the Nusselt number. Commonly used correlations are based in experiments performed at low Rayleigh numbers and/or using isothermal walls in simplified geometries. Here, this work improves on the accuracy of natural convection heat transfer correlations in support for HTGR designs. These correlations include both local and average Nusselt numbers as a function of the global Rayleigh number, the local Rayleigh number, and the temperature profile at the hot wall of the RCCS. In the absence of dedicated experiments and the difficulty of performing high-fidelity simulations at realistic Rayleigh numbers, the data to fit the correlations are generated with Computational Fluid Dynamics (CFD) using Reynolds Averaged Navier-Stokes (RANS) models. First, a careful selection of the RANS turbulence model is performed by comparing the results obtained with different RANS turbulence models against high fidelity simulations of natural convection at $Ra \ 1 \times 10^{11}$ in a rectangular cavity. Next, the selected model is used to perform simulations of an HTGR cavity at different high Rayleigh numbers $\in [6.1 \times 10^{11},2.9 \times 10^{13}]$ to encompass several HTGR designs, assuming an isothermal RPV wall. The results obtained are used to fit a correlation for the average and space-varying Nusselt number as a function of the global and local Rayleigh numbers via a sparsity-promoting least-squares method. The selected RANS model is then used to perform simulations of a PBMR 400 HTGR cavity with the temperature profiles at the RPV wall obtained during a PLOFC transient. We use the results obtained to fit a temperature-dependent correction to the space-varying Nusselt number with the sparsity-promoting least-squares method. The results obtained in this work, enable system-level codes, such as Pronghorn, to perform higher-fidelity simulations of the heat exchange process in the RCCS while still maintaining a low computational cost.

42 ENGINEERING↗
DOE OSTI2024

A realistic TRACE PWR LOCA model with application to high-burnup analysis

This paper presents a TRACE model of a postulated large-break loss-of-coolant accident (LBLOCA) event in a four-loop pressurized water reactor (PWR). The input files have been made publicly available and serve as a starting point for researchers to improve upon or apply to their purposes. The model, based on a legacy PWR model, contains numerous improvements and modifications consistent with US Nuclear Regulatory Commission LBLOCA analysis guidelines. The model is applied to analyze high-burnup (>62 GWD/MTU) fuel behavior during LBLOCA, improving on previous work to provide realistic thermal hydraulic predictions for future fuel performance analyses and experiments related to fission fragment, relocation, and dispersal (FFRD). Sensitivity studies are presented to quantify the impact of the vessel-modeling approach, core radial discretization, and other phenomena. In conclusion, the model is intended for research purposes and contains sufficient plant geometric, operational, and safety system details to represent the main physical phenomena pertaining to LBLOCA.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Impacts of turbine and plant upsizing on the levelized cost of energy for offshore wind

Turbine and plant upsizing are major trends in offshore wind deployment, although the quantitative impact on project costs has not been well-characterized. The uncertain value of continued wind turbine and project growth limits the ability of the supply chain to prepare for future technology trends, leading to challenges in the realization of larger projects. This analysis explores the levelized cost of energy impacts of turbine ratings between 6 and 20 MW and plant capacities between 250 and 2,500 MW for fixed-bottom offshore wind using techno-economic cost models for foundation, electrical, installation, and operation and maintenance costs, along with annual energy production. We consider a nominal set of technology assumptions for all scenarios to isolate economies of size and scale without additional benefits from decreasing turbine capital costs, quantity discounts for larger projects, or optimized technology solutions. These results indicate that using a 20-MW wind turbine in a 2,500-MW power plant array can reduce the levelized cost of energy by over 23% relative to the global average turbine and plant size installed in 2019; primarily because of reductions in the balance-of-system and operation and maintenance costs. We also identify improved installation vessels, optimized export systems, and novel operation and maintenance strategies as additional cost reduction opportunities. These results suggest that upsizing represents a significant cost reduction opportunity for offshore wind energy and will continue to be a main factor in shaping the future of the sector.

17 WIND ENERGY↗
DOE OSTI2021

Economic solution for low carbon process heat: A horizontal, compact high temperature gas reactor

In 2018, nuclear energy generated 55% of United States’ and one third of the world’s carbon free electricity, making nuclear energy a key tool in efforts to mitigate climate change before 2050. However, the current nuclear technology, light water reactors (LWRs), is limited to 300°C, so it cannot be used to decarbonize industrial process heat which accounts for 12% of US greenhouse gas emissions. High temperature gas reactors (HTGRs) can meet the high temperature demand with carbon free nuclear heat. The estimated cost of HTGRs, such as the Next Generation Nuclear Plant (NGNP), are even higher than state-of-the-art LWRs. In this paper, we expanded our nuclear cost estimating tool to include HTGRs and find that the NGNP overnight capital costs were 32% higher than an advanced LWR per unit capacity. The higher cost will naturally result in larger risk to cost overrun as recently experienced by larger LWRs in western nations. With a design-to-build mindset to minimize cost and construction risk, we introduce the horizontal, compact HTGR (HC-HTGR). The reactor core and steam generator are mounted horizontally on rails and in-line with one another, decreasing the size of the reactor building relative to the power capacity four times when compared to traditional HTGRs. The HC-HTGR reduced overnight civil structure costs by 42%, indirect costs by 38%, and total capital costs by 20% from NGNP. We discussed the required engineering of new systems for the HC-HTGR including vessel supports, the reactor cavity cooling system, and steam generator design. Finally, we estimated the fuel and operations costs of the HC-HTGR, and a survey of low-carbon industrial process heat technology showed the HC-HTGR can deliver a highly competitive levelized cost of heat in the range of $6.13–12.48/GJ.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Smart culture medium optimization for recombinant protein production: Experimental, modeling, and AI/ML-driven strategies

Recombinant protein production (RPP) is central to biotechnology, where recombinant proteins are used as either end products or catalysts in the synthesis of chemicals, fuels, and materials. Among the major cost drivers, culture medium plays a pivotal role in determining protein yield and quality. This review presents a comprehensive perspective on the critical stages of “smart” culture medium optimization: planning, screening, modeling, optimization, and validation. In the planning stage, we examine the nutritional and energetic roles of medium components, including carbon, nitrogen, amino acids, salts, and trace metals, and their impacts on culture parameters such as pH, oxidative state, and osmolality. We highlight the variability in trace metal content due to water sources, culture vessels, and raw materials, which can substantially influence RPP. The screening stage covers Design of Experiments (DoE) approaches, assessing their theoretical basis, implementation, and limitations. For modeling, we describe methods that integrate experimental data to develop predictive models for smart medium formulation. Model-based optimization strategies can then be employed to select optimal media compositions for a given application. The validation stage aims to evaluate model predictions and provide feedback for model training and refinement. Finally, we survey mechanistic and artificial intelligence/machine learning (AI/ML)-driven models as integrated, transformational tools for predictive modeling of bioprocess conditions, nutrient availability, cellular metabolism, and protein quality, with the goal of optimizing culture media to enhance protein yields while reducing costs and environmental impact. We conclude by addressing the challenges of translating laboratory-scale medium optimization to industrial-scale settings and exploring future AI/ML-driven approaches that may overcome current bottlenecks and accelerate medium design for RPP. Overall, this review provides a unified framework for advancing smart medium design in RPP.

Artificial Intelligence/Machine Learning (AI/ML)↗
DOE OSTI2021

In-situ X-ray and visual observation of foam morphology and behavior at the batch-melt interface during melting of simulated waste glass

We report to attain a basic understanding of the primary foam structure and behavior, which affects the heat and mass transfer and the efficiency of the glass melting process, we investigated the primary foam layer under the glass batch floating on molten glass. The primary foam affects mass transfer during batch melting, in turn affecting the melting process. The recently performed direct in-situ three-dimensional X-ray computed tomography of the batch melting in a laboratory-scale melter vessel allowed us to visualize the features of the reacting batch layer and the foam that develops at its bottom, though with an insufficient resolution of images. In this study, we obtained better temporal and spatial resolution using the two-dimensional X-ray radiography and visual observation of the structure and behavior of transient primary foam as it formed and decayed. As soon as the batch was charged onto the melt surface, foam bubbles began to evolve, grow, and coalesce, forming a primary foam layer, 5-10 mm thick, within tens of seconds. This foam layer was sustained by ongoing gas evolving reactions counterbalanced by bubble coalescence into cavities that moved sideways and escaped to the atmosphere. Eventually, the entire remaining batch turned into foam that gradually decayed at the melt surface. The decay rate agreed with literature observations of surface foam produced by secondary foaming.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling gas release from a Bingham plastic slurry and deconvoluting measured data

Physics-based models for predicting the off-gassing characteristics of agitated slurries are presented. This approach decomposes the system into two separate but coupled slurry and headspace models. The physics driving bubble transport through the slurry and gas mixing within the headspace are discussed. An analytical expression for predicting the time evolution of the headspace concentration using first principles theory is also presented. Predictions from the numerical models, as well as expectations from the analytical solution, both agree with measured off gassing data for two different experimental operating conditions. After benchmarking the numerical model predictions against experimental data, the model was used to make predictions for gas release from a full-scale vessel and to perform sensitivity analyses to examine the sensitivity of gas release to parameters such as yield stress, consistency index, slurry density, bubble size, bubble concentration, and impeller speed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Mobility of heavy rare earth elements in magmatic-hydrothermal systems: Experimental determination of DyPO 4 solubility in supercritical fluids

Dysprosium (Dy) is part of the heavy rare earth elements (REE) and a critical component in the production of high-performance super magnets used in wind turbines, electric vehicles, and other green technologies. The HREE phosphate, xenotime, is commonly associated with hydrothermal systems, where the mobility, fractionation, and deposition of REE are controlled by the stability of aqueous complexes and solubility of REE minerals which depend on temperature, pressure, and fluid composition (salinity, pH, and ligand availability). Here, we conducted a series of synthetic DyPO 4 solubility experiments in NaCl-HCl-bearing aqueous solutions (pH of 2 at 25 °C) from 500 to 700 °C and 1.5 kbar using externally heated pressure vessels. DyPO 4 displays a strong prograde solubility with temperature across all studied fluid salinities (0–0.5 m NaCl). The DyPO₄ solubility isotherms at 500 °C, 600 °C, and 700 °C show a complex relationship with salinity where DyPO₄ solubility is highest (39.2–1552 ppm at 500–700 °C) in 0 m NaCl solutions, decreases strongly (21–331 ppm at 500–700 °C) in the 0.06 m NaCl solutions and remains relatively constant in the 0.25 m (42.8–248 ppm) and 0.5 m NaCl (40.2–124 ppm) solutions. Thermodynamic modeling suggests that pH increases as a function of temperature and salinity, and controls solubility due to the stability of chloride complexes (i.e., DyCl +2 and DyCl 2 + ) at 500–600 °C, transitioning to hydroxyl complexes (i.e., Dy(OH) 3 0 ) dominating at 700 °C and relatively alkaline pH. Comparison with NdPO 4 solubility data indicates that the light REE in monazite is significantly more soluble than the heavy REE in xenotime in saline fluids at high temperature (500–700 °C), implying efficient light/heavy REE fractionation in supercritical fluids. The lower solubility of DyPO 4 relative to NdPO 4 suggests that at high temperatures, acidic (pH 2–4), low-salinity (∼5 wt% NaCl) fluids will favor the precipitation of xenotime over monazite as it will cool from 700 °C to below 500 °C. These observations align with paragenetic mineral assemblages in NYF pegmatites (e.g., Baveno, Italy), where xenotime commonly immobilizes heavy REE during the high-temperature hydrothermal stages.

58 GEOSCIENCES↗
DOE OSTI2025

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation↗