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DOE OSTI2017

Monitoring nanoparticle synthesis in a carbon arc discharge environment, in situ

This work presents experimental and theoretical studies of gas-phase synthesis of fullerenes and carbon nanoparticles in the presence of an atmospheric-pressure, arc discharge plasma. Carbon arc discharges have been used for synthesizing carbon nanotubes for over 25 years, and have the potential for economically synthesizing industrial-scale quantities of fullerenes. However, the efficiency and selectivity of fullerene synthesis with carbon arc discharges are quite low. Optimizing carbon arc discharges for fullerene synthesis requires a thorough understanding of the dynamics behind gas-phase nanoparticle synthesis in the presence of an arc discharge plasma. We built a carbon arc discharge setup to study nanoparticle and fullerene synthesis. The laser-induced incandescence (LII) diagnostic was applied for monitoring nanoparticle synthesis, in situ. The LII diagnostic had previously been applied as a combustion diagnostic for in situ measurements of concentrations and sizes of soot particles in flame environments. Prior to the present study, it had never been applied for studying fullerenes, nor had it been applied to study nanoparticles in the presence of an atmospheric-pressure plasma. Therefore, experiments were designed that allowed for the calibration of the LII diagnostic with research-grade, arc-synthesized soot particles and carbon nanotubes. Additionally, the theory and models underpinning the LII diagnostic were adapted to include the presence of an atmospheric-pressure, arc-discharge plasma. Results presented in this work confirm the ability of the LII diagnostic to measure sizes of arc-synthesized nanoparticles in situ, and show the spatial location of high densities of arc-synthesized nanoparticles with respect to the arc discharge plasma. Determining the spatial location of nanoparticle synthesis and growth is crucial for understanding the background conditions (e.g. background gas temperature, electron densities ...) in which nanoparticles nucleate and grow in the arc discharge environment. Future work would involve combining the LII diagnostic with other laser-based diagnostics (e.g. Rayleigh scattering, laser-induced fluorescence) for a more comprehensive study of gas-phase nanoparticle synthesis and investigating fundamental basic-science questions related to low temperature plasma physics, and laser-nanoparticle interactions.

Nanotechnology↗

NASA NTRS2003

Global Changes of the Water Cycle Intensity

In this study, we evaluate numerical simulations of the twentieth century climate, focusing on the changes in the intensity of the global water cycle. A new diagnostic of atmospheric water vapor cycling rate is developed and employed, that relies on constituent tracers predicted at the model time step. This diagnostic is compared to a simplified traditional calculation of cycling rate, based on monthly averages of precipitation and total water content. The mean sensitivity of both diagnostics to variations in climate forcing is comparable. However, the new diagnostic produces systematically larger values and more variability than the traditional average approach. Climate simulations were performed using SSTs of the early (1902-1921) and late (1979- 1998) twentieth century along with the appropriate C02 forcing. In general, the increase of global precipitation with the increases in SST that occurred between the early and late twentieth century is small. However, an increase of atmospheric temperature leads to a systematic increase in total precipitable water. As a result, the residence time of water in the atmosphere increased, indicating a reduction of the global cycling rate. This result was explored further using a number of 50-year climate simulations from different models forced with observed SST. The anomalies and trends in the cycling rate and hydrologic variables of different GCMs are remarkably similar. The global annual anomalies of precipitation show a significant upward trend related to the upward trend of surface temperature, during the latter half of the twentieth century. While this implies an increase in the hydrologic cycle intensity, a concomitant increase of total precipitable water again leads to a decrease in the calculated global cycling rate. An analysis of the land/sea differences shows that the simulated precipitation over land has a decreasing trend while the oceanic precipitation has an upward trend consistent with previous studies and the available observations. The decreasing continental trend in precipitation is located primarily over tropical land regions, with some other regions, such as North America experiencing an increasing trend. Precipitation trends are diagnosed further using the water tracers to delineate the precipitation that occurs because of continental evaporation, as opposed to oceanic evaporation. These diagnostics show that over global land areas, the recycling of continental moisture is decreasing in time. However, the recycling changes are not spatially uniform so that some regions, most notably over the United States, experience continental recycling of water that increases in time.

Bosilovich, Michael G.↗

DOE OSTI2022

CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

Abstract. Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes (i.e., phenomena) such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods.

58 GEOSCIENCES↗

DOE OSTI2015

A wave model of refraction of laser beams with a discrete change in intensity in their cross section and their application for diagnostics of extended nonstationary phase objects

A beam model with a discrete change in the cross-sectional intensity is proposed to describe refraction of laser beams formed on the basis of diffractive optical elements. In calculating the wave field of the beams of this class under conditions of strong refraction, in contrast to the traditional asymptotics of geometric optics which assumes a transition to the infinite limits of integration and obtaining an analytical solution, it is proposed to calculate the integral in the vicinity of stationary points. This approach allows the development of a fast algorithm for correct calculation of the wave field of the laser beams that are employed in probing and diagnostics of extended optically inhomogeneous media. Examples of the algorithm application for diagnostics of extended nonstationary objects in liquid are presented. (laser beams)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Evaluate the impact of sensor accuracy on model performance in data-driven building fault detection and diagnostics using Monte Carlo simulation

The performance of data-driven fault detection and diagnostics (FDD) is heavily dependent on sensors. However, sensor inaccuracy and sensor faults are pervasive in building operation: inaccurate and missing sensor readings deteriorate FDD performance; sensor inaccuracy will also affect the selection of sensor for data-driven FDD in the model training process, which is another key factor of data-driven FDD performance. Sensor accuracy and sensor selection individually are well-studied research topics in this field, but the impact of sensor accuracy on sensor selection and its further impact on FDD performance has not been evaluated and quantified. In this paper, we developed a novel analysis methodology that comprehensively evaluates sensor fault on sensor selection and FDD accuracy. Monte Carlo simulation is applied to deal with multiple stochastic sensor inaccuracy and provide probabilistic analysis results of the impact of sensor inaccuracy on sensor selection and FDD accuracy. This methodology focuses on the net impact of fault states across a full sensor set. The developed methodology can be used for the early-stage sensor design and operation-stage sensor maintenance. Furthermore, a case study is conducted to demonstrate the analysis methodology using a commercial building model crated to Flexible Research Platform located at Oak Ridge National Laboratory, USA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Brachytherapy structural shielding calculations using Monte Carlo generated, monoenergetic data

Purpose: To provide a method for calculating the transmission of any broad photon beam with a known energy spectrum in the range of 20–1090 keV, through concrete and lead, based on the superposition of corresponding monoenergetic data obtained from Monte Carlo simulation. Methods: MCNP5 was used to calculate broad photon beam transmission data through varying thickness of lead and concrete, for monoenergetic point sources of energy in the range pertinent to brachytherapy (20–1090 keV, in 10 keV intervals). The three parameter empirical model introduced byArcher et al. [“Diagnostic x-ray shielding design based on an empirical model of photon attenuation,” Health Phys. 44, 507–517 (1983)] was used to describe the transmission curve for each of the 216 energy-material combinations. These three parameters, and hence the transmission curve, for any polyenergetic spectrum can then be obtained by superposition along the lines of Kharrati et al. [“Monte Carlo simulation of x-ray buildup factors of lead and its applications in shielding of diagnostic x-ray facilities,” Med. Phys. 34, 1398–1404 (2007)]. A simple program, incorporating a graphical user interface, was developed to facilitate the superposition of monoenergetic data, the graphical and tabular display of broad photon beam transmission curves, and the calculation of material thickness required for a given transmission from these curves. Results: Polyenergetic broad photon beam transmission curves of this work, calculated from the superposition of monoenergetic data, are compared to corresponding results in the literature. A good agreement is observed with results in the literature obtained from Monte Carlo simulations for the photon spectra emitted from bare point sources of various radionuclides. Differences are observed with corresponding results in the literature for x-ray spectra at various tube potentials, mainly due to the different broad beam conditions or x-ray spectra assumed. Conclusions: The data of this work allow for the accurate calculation of structural shielding thickness, taking into account the spectral variation with shield thickness, and broad beam conditions, in a realistic geometry. The simplicity of calculations also obviates the need for the use of crude transmission data estimates such as the half and tenth value layer indices. Although this study was primarily designed for brachytherapy, results might also be useful for radiology and nuclear medicine facility design, provided broad beam conditions apply.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2026

Radiation modeling and experimental validation of sub-cyclotron frequency microwave synchrotron radiation as a diagnostic tool for runaway electrons in present and future tokamaks

The microwave synchrotron radiation in the sub-cyclotron frequency region has been systematically validated as a diagnostic method for runaway electrons (>1 MeV) with radiation modeling and experiments on the DIII-D tokamak. Experimental observations reveal that sub-cyclotron frequency microwave radiation emerges only after runaway electrons are excited during plasma disruptions. Electron gyro-magnetic radiation modeling confirms that only runaway electrons with energies exceeding 1 MeV can emit radiation in the observed sub-cyclotron frequency band on DIII-D. The synchrotron Razin and Beaming effects are modeled in both the sub-cyclotron and standard Electron Cyclotron Emission (ECE) frequency region. Due to the pronounced beaming effect, the modeling supports that a standard ECE system is insensitive to synchrotron radiation from beamed runaway electrons (p ∥ >> p ⟂ ), but very sensitive to ECE radiation from isotropic suprathermal electrons (100 keV or less). DIII-D experiments further show that combining ECE and sub-cyclotron receivers reveals new insights into transient runaway dynamics during the plateau phase. Certain transient crash events appear only in the sub-cyclotron band or lead to opposite changes on the sub-cyclotron and standard ECE signals, supporting models where transient MHD events can exert a different effect on electrons of different energy levels. This novel diagnostic technique offers a powerful tool for studying and detecting runaway electron dynamics in both present-day and high-field future tokamaks. The diagnostic approach has been extrapolated to the SPARC tokamak, where sub-cyclotron radiation is predicted to respond sensitively and solely to runaway electrons during SPARC’s L-mode startup phase.

Yu, Guanying [Hefei Comprehensive National Science↗

DOE OSTI2025

Mesoscale Convective Systems Tracking Method Intercomparison (MCSMIP): Application to DYAMOND Global km‐Scale Simulations

Abstract Global kilometer‐scale models represent the future of Earth system modeling, enabling explicit simulation of organized convective storms and their associated extreme weather. Here, we comprehensively evaluate tropical mesoscale convective system (MCS) characteristics in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) simulations for both summer and winter phases. Using 10 different feature trackers applied to simulations and satellite observations, we assess MCS frequency, precipitation, and other key characteristics. Substantial differences (a factor of 2–3) arise among trackers in observed MCS frequency and their precipitation contribution, but model‐observation differences in MCS statistics are more consistent across trackers. DYAMOND models are generally skillful in simulating tropical mean MCS frequency, with multi‐model mean biases ranging from −2%–8% over land and −8%–8% over ocean (summer vs. winter). However, most DYAMOND models underestimate MCS precipitation amount (23%) and their contribution to total precipitation (17%). Biases in precipitation contributions are generally smaller over land (13%) than over ocean (21%), with moderate inter‐model variability. While models better simulate MCS diurnal cycles and cloud shield characteristics, they overestimate MCS precipitation intensity and underestimate stratiform rain contributions (up to a factor of 2), particularly over land, albeit observational uncertainties exist. Additionally, models exhibit a wide range of precipitable water in the tropics compared to reanalysis and satellite observations, with many models showing exaggerated sensitivity of MCS precipitation intensity to precipitable water. The MCS metrics developed here provide process‐oriented diagnostics to guide future model development.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Arctic Amplification: Process Drivers and Sources of Uncertainty

Arctic amplification (AA) is a coupled atmosphere-sea ice-ocean process. This understanding has evolved from the early concept of AA, as a consequence of snow ice line progressions, through more than a century of research that has clarified the relevant processes and driving mechanisms of AA. The predictions made by early modeling studies, namely the fall/winter maximum, bottom-heavy structure, the prominence of surface albedo feedback, and the importance of stable stratification have withstood the scrutiny of multi-decadal observations and more complex models. Yet, the uncertainty in Arctic climate projections is larger than in any other region of the planet, making the assessment of high-impact, near-term regional changes difficult or impossible. Reducing this large spread in Arctic climate projections requires a quantitative process understanding. This presentation synthesizes current knowledge of AA and describes a set of recommendations to guide future research. It briefly reviews the history of AA science, summarizes observed Arctic changes, discusses modeling approaches and feedback diagnostics, and assesses the current understanding of the most relevant feedbacks to AA. These sections culminate in a conceptual model of the fundamental physical mechanisms causing AA and a collection of recommendations to accelerate progress towards reduced uncertainty in Arctic climate projections. Our conceptual model highlights the need to account for local feedback and remote process interactions within the context of the annual cycle to constrain projected AA.

Patrick C Taylor↗

DOE OSTI2023

A smart alarm for particle accelerator beamline operations

We present the initial results of a proof-of-concept 'smart alarm' for the Continuous Electron Beam Accelerator Facility injector beamline at Jefferson Lab. To minimize machine downtime and improve operational efficiency, an autonomous alarm system able to identify and diagnose unusual machine states is needed. Our approach leverages a trained neural network capable of alerting operators (a) when an anomalous condition exists in the beamline and (b) identifying the element setting that is the root cause. The tool is based on an inverse model that maps beamline readings (diagnostic readbacks) to settings (beamline attributes operators can modify). The model takes as input readings from the machine and computes machine settings which are compared to control setpoints. Instances where predictions differ from setpoints by a user-defined threshold are flagged as anomalous. Given data corresponding to 354 anomalous injector configurations, the model can narrow the root cause of an anomalous condition to three potential candidates with 94.6% accuracy. Furthermore, compared to the current method of identifying anomalous conditions which raises an alarm when machine parameters drift outside their normal tolerances, the data-driven model can identify 83% more anomalous conditions.

43 PARTICLE ACCELERATORS↗

DOE OSTI2015

Practical Use of Computationally Frugal Model Analysis Methods

Computationally frugal methods of model analysis can provide substantial benefits when developing models of groundwater and other environmental systems. Model analysis includes ways to evaluate model adequacy and to perform sensitivity and uncertainty analysis. Frugal methods typically require 10s of parallelizable model runs; their convenience allows for other uses of the computational effort. We suggest that model analysis be posed as a set of questions used to organize methods that range from frugal to expensive (requiring 10,000 model runs or more). This encourages focus on method utility, even when methods have starkly different theoretical backgrounds. We note that many frugal methods are more useful when unrealistic process-model nonlinearities are reduced. Inexpensive diagnostics are identified for determining when frugal methods are advantageous. Examples from the literature are used to demonstrate local methods and the diagnostics. We suggest that the greater use of computationally frugal model analysis methods would allow questions such as those posed in this work to be addressed more routinely, allowing the environmental sciences community to obtain greater scientific insight from the many ongoing and future modeling efforts

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1983

Stochastic models for atomic clocks

For the atomic clocks used in the National Bureau of Standards Time Scales, an adequate model is the superposition of white FM, random walk FM, and linear frequency drift for times longer than about one minute. The model was tested on several clocks using maximum likelihood techniques for parameter estimation and the residuals were acceptably random. Conventional diagnostics indicate that additional model elements contribute no significant improvement to the model even at the expense of the added model complexity.

Barnes, J. A.↗

NASA NTRS1998

Observation and Modeling of the Solar Transition Region: A Quasi-Static Loops Model with Implications for Heating the Lower Transition Region - 1

We report on observations of the solar atmosphere in several extreme ultraviolet and far-ultraviolet bandpasses obtained by the Multi-Spectral Solar Telescope Array, a rocket borne spectroheliograph, on flights in 1987, 1991, and 1994, spanning the last solar maximum. Quiet sun emission observed in the 171 A - 175 A bandpass, which includes lines of 0Ov, O vi, Fe ix, and Fe x, has been analyzed to test models of the temperatures and geometries of the structures responsible for this emission. Analyses of intensity variations above the solar limb reveal scale heights consistent with a quiet sun plasma temperature of 500 000 K less than or equal to T(sub e) less than or equal to 800 000 K. Intensity modulations in the quiet sun are observed to occur on a scale comparable to the supergranular scale. The structures responsible for the quiet sun EUV emission are modeled as small quasi-static loops. We find that the emission predicted by loop models with maximum temperatures between 700 000 K and 900 000 K are consistent with our observations. We also present a preliminary comparison of the predictions of our models with observations of diagnostic spectral line ratios obtained from previous observers. We discuss the implications a distribution of loops of the type we model here would have for heating the lower transition region. Finally, in fight of the models we calculate here, we briefly review the current state of knowledge concerning the contributions thermal conduction from coronal (T(sub e) greater than or equal to 10(exp 6) K) and upper transition region (10(exp 5) K less than T(sub e) less than 10(esp 6) K) structures make to lower transition region emission. We argue that the evidence which has lead many authors to conclude that the interface of hotter and cooler plasmas makes a negligible contribution to lower transition region emission is much less compelling in light of recent observations and analyses. We further argue that it is the interface of chromospheric material with structures such as loops that have sub-coronal peak temperatures (i.e. less than 900 000 K) that makes the dominant contribution to lower transition region emission in the quiet sun.

Oluseyi, Hakeem M.↗

NASA NTRS2004

Explanation Constraint Programming for Model-based Diagnosis of Engineered Systems

We can expect to see an increase in the deployment of unmanned air and land vehicles for autonomous exploration of space. In order to maintain autonomous control of such systems, it is essential to track the current state of the system. When the system includes safety-critical components, failures or faults in the system must be diagnosed as quickly as possible, and their effects compensated for so that control and safety are maintained under a variety of fault conditions. The Livingstone fault diagnosis and recovery kernel and its temporal extension L2 are examples of model-based reasoning engines for health management. Livingstone has been shown to be effective, it is in demand, and it is being further developed. It was part of the successful Remote Agent demonstration on Deep Space One in 1999. It has been and is being utilized by several projects involving groups from various NASA centers, including the In Situ Propellant Production (ISPP) simulation at Kennedy Space Center, the X-34 and X-37 experimental reusable launch vehicle missions, Techsat-21, and advanced life support projects. Model-based and consistency-based diagnostic systems like Livingstone work only with discrete and finite domain models. When quantitative and continuous behaviors are involved, these are abstracted to discrete form using some mapping. This mapping from the quantitative domain to the qualitative domain is sometimes very involved and requires the design of highly sophisticated and complex monitors. We propose a diagnostic methodology that deals directly with quantitative models and behaviors, thereby mitigating the need for these sophisticated mappings. Our work brings together ideas from model-based diagnosis systems like Livingstone and concurrent constraint programming concepts. The system uses explanations derived from the propagation of quantitative constraints to generate conflicts. Fast conflict generation algorithms are used to generate and maintain multiple candidates whose consistency can be tracked across multiple time steps.

Narasimhan, Sriram↗

DOE OSTI2018

Synthetic diagnostic for assessing spatial averaging of charge exchange recombination spectroscopy measurements

A synthetic charge exchange recombination spectroscopy diagnostic based on the FIDASIM modeling suite has been created for the DIII-D tokamak. This synthetic diagnostic assumes that the ions have Maxwellian distribution functions on each flux surface and models emission from charge exchange events between the beam neutrals and a fully ionized impurity. This work was motivated by the observation of non-Gaussian spectra that may be caused by spatial averaging, atomic physics, or non-Maxwellian distribution functions. Measurements of non-Gaussian spectra commonly observed in the high confinement mode pedestal and in plasmas with large core gradients are compared to the synthetic diagnostic. Spatial averaging alone cannot account for the observations in these two cases, opening up the possibility of there being other causes such as non-Maxwellian distribution functions. Here, the synthetic diagnostic has also been used to resolve a long-standing issue: it is shown that the lower temperatures measured by using vertical view chords relative to tangential view chords are due to increased spatial averaging for vertical views due to the DIII-D neutral beams being approximately twice as tall as they are wide.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1986

An analysis of the high-latitude thermospheric wind pattern calculated by a thermospheric general circulation model. II - Neutral parcel transport

A diagnostic package developed to analyze runs made by the National Center for Atmospheric Research thermosphere general circulation model is used to calculate neutral parcel trajectories in the high-latitude E and F regions. Parcel trajectories are presented for a number of different cases to illustrate the main characteristics of F region parcel transport in the winter high-latitude region. Several examples of E region parcel trajectories are similarly analyzed, concentrating on both the southern (summer) and northern (winter) regions. F region parcel trajectories are calculated backward in time from passage over a given geographical location to illustrate the 'genesis' of those parcels whose velocities can be monitored from a ground-based Fabry-Perot observatory.

Killeen, T. L.↗

DOE OSTI2014

The ITER 3D Magnetic Diagnostic Response to Applied n=3 and n=4 RMP's

The ITER magnetic diagnostic response to applied n=3 and n=4 RMPs has been calculated for the 15MA scenario. The VMEC code was utilized to calculate free boundary 3D ideal MHD equilibria, where the non-stellarator symmetric terms were included in the calculation. This allows an assessment to be made of the possible boundary displacements due to RMP application in ITER. As the VMEC code assumes a continuous set of nested flux surface, the possibility of island and stochastic region formation is ignored. At the start of the current at-top (L-Mode) application of n = 4 RMP's indicates approximately 1 cm peak-to-peak displacements on the low field side of the plasma while later in the shot (H-mode) perturbations as large as 3 cm are present. Forward modeling of the ITER magnetic diagnostics indicates significant non-axisymmetric plasma response, exceeding 10% the axisymmetric signal in many of the flux loops. Magnetic field probes seem to indicate a greater robustness to 3D effects but still indicate large sensitivities to 3D effects in a number of sensors. Forward modeling of the diagnostics response to 3D equilibria allows assessment of diagnostics design and control scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks

Advances in computational science offer a principled pipeline for predictive modeling of cardiovascular flows and aspire to provide a valuable tool for monitoring, diagnostics and surgical planning. Such models can be nowadays deployed on large patient-specific topologies of systemic arterial networks and return detailed predictions on flow patterns, wall shear stresses, and pulse wave propagation. However, their success heavily relies on tedious pre-processing and calibration procedures that typically induce a significant computational cost, thus hampering their clinical applicability. Here, we put forth a machine learning framework that enables the seamless synthesis of non-invasive in-vivo measurement techniques and computational flow dynamics models derived from first physical principles. We illustrate this new paradigm by showing how one-dimensional models of pulsatile flow can be used to constrain the output of deep neural networks such that their predictions satisfy the conservation of mass and momentum principles. Once trained on noisy and scattered clinical data of flow and wall displacement, these networks can return physically consistent predictions for velocity, pressure and wall displacement pulse wave propagation, all without the need to employ conventional simulators. A simple post-processing of these outputs can also provide a relatively cheap and effective way for estimating Windkessel model parameters that are required for the calibration of traditional computational models. Finally, the effectiveness of the proposed techniques is demonstrated through a series of prototype benchmarks, as well as a realistic clinical case involving in-vivo measurements near the aorta/carotid bifurcation of a healthy human subject.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗