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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Engineering and evaluation of FXa bypassing agents that restore hemostasis following Apixaban associated bleeding

Direct oral anticoagulants (DOACs) targeting activated factor Xa (FXa) are used to prevent or treat thromboembolic disorders. DOACs reversibly bind to FXa and inhibit its enzymatic activity. However, DOAC treatment carries the risk of anticoagulant-associated bleeding. Currently, only one specific agent, andexanet alfa, is approved to reverse the anticoagulant effects of FXa-targeting DOACs (FXaDOACs) and control life-threatening bleeding. However, because of its mechanism of action, andexanet alfa requires a cumbersome dosing schedule, and its use is associated with the risk of thrombosis. Here, we present the computational design, engineering, and evaluation of FXa-variants that exhibit anticoagulation reversal activity in the presence of FXaDOACs. Our designs demonstrate low DOAC binding affinity, retain FXa-enzymatic activity and reduce the DOAC-associated bleeding by restoring hemostasis in mice treated with apixaban. Importantly, the FXaDOACs reversal agents we designed, unlike andexanet alfa, do not inhibit TFPI, and consequently, may have a safer thrombogenic profile.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A model investigation of the impact of lower hybrid wave scattering angle on current drive profile in EAST and Alcator C-Mod

Lower hybrid current drive (LHCD) is beneficial for developing a steady-state operation scenario in a tokamak. This paper conducts a modeling investigation to identify an optimum rotation angle of the initial lower hybrid perpendicular (to the background magnetic field $\overrightarrow{B}$) wavevector for best matching the experimental RF current profile. It is hypothesized that central RF power deposition widely observed in the present-day LHCD experiments arises from wave scattering by turbulence. In a standard model without considering such interactions, the predicted power deposition profile is generally broad with off-axis peaking, not in agreement with experimental observations. A heuristic approach is adopted by introducing a spectral broadening mechanism by modifying the initial orientation of the perpendicular wavevector. The ray-tracing/Fokker–Planck solver GENRAY/CQL3D is utilized within the python-based π-scope framework. A focus is given to identify the perpendicular wavenumber orientation angle with respect to the magnetic surface normal vector at the initial ray location. Our modeling study shows that rotating the perpendicular wavevector in such a way as to increase the initial poloidal component is effective in reproducing the centrally peaked current profile observed in normal shear plasmas on both EAST and C-Mod. These waves can readily be absorbed to the central plasma, which reduces the sensitivity of the power deposition profile to a slight change of the plasma condition. The same approach is also found to help broaden the off-axis power deposition profile in a reverse-shear EAST plasma, leading to a better agreement with the experiment. The results presented here suggest that spectral modification arising from edge density fluctuations in a tokamak may need to be considered in understanding wave propagation and absorption. A further experimental and theoretical/modeling study is vital as a reverse approach is adopted in this study. Finally, our work suggests that mitigation or control measures are critical for parasitic effects occurring on the first pass in a reactor regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Description of global EGAM in the maximum of local frequency during current ramp-up discharges in DIII-D

Energetic-particle-induced geodesic acoustic modes, EGAMs (Fu, Phys. Rev. Let., vol. 101, 2008, pp. 185002), driven by neutral beam injection (NBI), have been observed in many DIII-D tokamak experiments (Nazikian et al., Phys. Rev. Lett., vol. 101, 2008, pp. 185001). This mechanism has been theoretically investigated in (Qiu et al., Plasma Phys. Control. Fusion, vol. 52, 2010, pp. 095003), using a sharp energetic particle distribution function, and in (Qu et al., Plasma Phys. Control. Fusion, vol. 59, 2017, pp. 055018), where the dispersion relation and eigenmode behaviour were obtained for the situation of early beam scenario, that is, for times smaller than the beam slowing down time. In this work, we extend these studies determining the eigenmode for beyond the slowing down time, in a scenario with reverse safety factor q profile, where a small concentration of energetic ions can produce an off-axis maximum in the GAM dispersion relation. Here, the characteristics of EGAM are analytically studied with the drift kinetic equation together with the MHD code NOVA. The toroidal energetic ion transit frequency, coupled with the GAM frequency, produces the maximum in the dispersion relation where the eigenmode can be found. The quantitative correspondence of experimental results with the predictions of the proposed model is analysed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Anodized Aluminum Oxide Membrane Ionic Memristors

Memory effect in ion transport (IT) at the solid–solution interface is uniquely attractive in that the conductance depends on or “memorizes” the previous states. Hysteretic and rectified transport properties offer exciting potential to developing advanced iontronics and neuromorphic functions, improving the efficiency of energy conversion and electrochemical processes, and overcoming the selectivity-throughput bottleneck in the enrichment of low abundant species for environment- and energy-friendly separations, among others. Herein, memory effects are discovered in the rectified electrokinetic IT through anodized aluminum oxide (AAO) membranes containing densely packed highly ordered nanochannels (10 10 per cm 2 ). Characteristic memristor responses of pinched current–potential loops are resolved in voltammetric experiments and successfully reproduced through finite element simulation. Excitatory and inhibitory conductance states are shown to arise from the enrichment and depletion of mobile charge carriers. Structurewise, the transport symmetry is broken by the barrier oxide layer (BOL) on the one end of the cylindrical nanochannels across the AAO membranes. Charge selectivity is attributed to the gradient(s) of the space charge density across the BOL characterized by depth profiling via X-ray photoelectron spectroscopy analysis. The space charge gradient(s) overcomes the fundamental limitation of widely exploited surface charge effects to enable intense rectification and hysteresis prevailing at very high ionic concentrations up to 1–2 M. A new strategy is developed for controlling the preferential IT direction and selectivity via counterion intercalation and extraction/exchange. Mechanistic understanding is further confirmed through parameter variations such as potential scan rate and ionic strength, which also demonstrates convenient controls of the related functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Autoignition of cyclohexane at low-to-intermediate temperatures: Rapid compression machine experiments and improved comprehensive chemical kinetic model

Cycloalkanes are an important class of hydrocarbons found in conventional and alternative transportation fuels. Being one of the simplest practical cycloalkanes, cyclohexane is often used as a surrogate in studies to understand the oxidation, ignition, and sooting characteristics of cycloalkanes more broadly. Although cyclohexane has been extensively studied, very limited datasets for cyclohexane oxidation at low-to-intermediate temperatures are available in the literature. Moreover, the literature autoignition data from rapid compression machines (RCMs) did not provide information on volume histories or experimental heat transfer characteristics which can significantly impact model predictions, thereby hindering the detailed validation of chemical kinetic models. It has also been observed that the cyclohexane kinetic models developed so far are not able to predict the literature data across a wide range of operating and mixture conditions. Hence, further studies are recommended to understand and improve model predictions for cyclohexane oxidation. In this study, RCM experiments were conducted using cyclohexane/air mixtures at varying compressed pressures (P C =15, 20, and 30 bar), equivalence ratios (ϕ=0.5, 1.0, and 2.0), and compressed temperatures (T C =670–960 K). The current RCM results of cyclohexane were found to complement well with the literature data, with the first-stage IDTs at high pressures and volume histories at all test conditions being first reported for better development and validation of chemical kinetic models. Additionally, a detailed chemical kinetic model for the cyclohexane oxidation has been developed and validated using both newly acquired experimental IDTs in this study and literature experimental studies (IDTs in RCMs and STs, species profiles in jet-stirred reactors, and laminar burning velocities). Unlike literature models, the proposed model was observed to provide an overall better prediction for experimental results over a wide range of conditions. Chemical kinetic analysis of the developed model was further conducted to identify the reaction pathways controlling the autoignition of cyclohexane.

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

Effect of thermal treatments on electrochemical behavior of binder jetted 17-4 PH stainless steel

Binder jetted 17–4 PH stainless steel was post-processed to relate heat treatment, microstructure, and corrosion in 3.5 wt% NaCl. Specimens were sintered at 1380 or 1400 °C, solution-annealed at 1055 °C for 1 h, and aged at 482 °C for 1 h. Here, as-sintered parts showed α′-martensitic matrix with a δ-ferrite network and Cu-rich precipitates in ferrite; inclusions (MnS, NbC) promoted localized attack. solutionizing redistributed elements and reduced ferrite, while aging generated coherent Cu nano-precipitates. Corrosion resistance was highly sensitive to post-processing in which aged specimens exhibited the lowest corrosion current density and formed a thicker, stable Cr 2 O 3 -rich passive film, whereas sintered specimens degraded most. Pitting potential depended on sintering temperature and microstructure, with 1400 °C sintering yielding more positive pitting potentials and the best overall performance after aging. Although the 1400-solutionized condition showed a relatively noble pitting response versus 1380-solutionized, it displayed unstable corrosion kinetics attributed to an imperfect passive film linked to higher NbC density. XPS depth profiles corroborated these trends, showing thicker, more continuous Cr 2 O 3 in aged states and discontinuous/thinning oxides in less resistant conditions. Practically, high-temperature sintering (∼1400 °C) followed by solutionizing and aging is recommended, with further gains expected from reducing NbC/MnS populations and porosity via powder and process control.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The age distribution of global soil carbon inferred from radiocarbon measurements

Soils contain more carbon than the atmosphere and vegetation combined. An increased flow of carbon from the atmosphere into soil pools could help mitigate anthropogenic emissions of carbon dioxide and climate change. Yet we do not know how quickly soils might respond because the age distribution of soil carbon is uncertain. Here we used 789 radiocarbon (Δ 14 C) profiles, along with other geospatial information, to create globally gridded datasets of mineral soil Δ 14 C and mean age. We found that soil depth is a primary driver of Δ 14 C, whereas climate (for example, mean annual temperature) is a major control on the spatial pattern of Δ 14 C in surface soil. Integrated to a depth of 1m, global soil carbon has a mean age of 4,830 ± 1,730 yr, with older carbon in deeper layers and permafrost regions. In contrast, vertically resolved land models simulate Δ 14 C values that imply younger carbon ages and a more rapid carbon turnover. Overall, our data-derived estimates of older mean soil carbon age suggest that soils will accumulate less carbon than predicted by current Earth system models over the twenty-first century. Reconciling these models with the global distribution of soil radiocarbon will require a better representation of the mechanisms that control carbon persistence in soils.

58 GEOSCIENCES↗
DOE OSTI2025

High-resolution lidar observations of sedimentation-induced size sorting of droplets near a laboratory cloud top

Cloud optical properties and precipitation, which are crucial to weather and climate, are strongly influenced by cloud microphysical properties that are still poorly understood. Here, we develop a high-resolution time-correlated single-photon-counting lidar and apply it to observe cloud microphysical properties at one-centimeter range resolution in a convection chamber under well-controlled conditions. Together with concurrent in-situ measurements and theoretical analysis, our lidar observations indicate that although turbulent mixing tends to homogenize the cloud in the bulk region, entrainment and sedimentation cause inhomogeneities in droplet concentrations near the cloud top. Specifically, the topmost region is directly affected by entrainment, and lidar profiles show clear evidence of entrained air and detrained cloud filament. The transition region below exhibits vertical size sorting of cloud droplets caused by sedimentation. Our results suggest that using a single sedimentation velocity for all cloud droplets, as is done in many atmospheric models, overlooks key physics relevant to the microphysical structure near the cloud top. In conclusion, our conceptual model used to describe these measurements can serve as a step toward improving the current modeling of processes in the cloud top region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Prediction of DIII-D Pedestal Structure from Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. An experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (ne) and electron temperature (Te) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (Ip), toroidal magnetic field (Bφ), neutral beam heating power (PNBI) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Designing a Particle Flow Control Apparatus

Flow control within a particle-based Concentrated Solar Power (CSP) system is essential in determining the heat transfer coefficient, and therefore, the power generation capability of these systems. There are three areas where particle flow control is significant: the receivers, storage tanks, and particle-sCO2 heat exchangers. The focus of this work is on designing a new mechanism to control the flow in the particle-sCO2 heat exchangers due to the simplicity and potential cost savings when compared to the other areas of interest. The goal is for this new design to have quicker response times in terms of particle flowrate than a slide gate or flow control valve, which are designs currently used. The design resembles that of a chuck mechanism within a drill where a rotation of the sleeve elicits movement of the jaws both vertically and horizontally to close the outlet area of the nozzle. Additionally, this design will utilize the current actuator that is already used within these heat exchangers to reduce the complexity of implementation. The jaws are designed to be closed at an angle of 76˚ which is just slightly steeper than the hopper leading to the mechanism. Furthermore, this design can be tuned to limit particle bridging and other particle flow phenomena that result in blockages. The prototypes were 3D printed out of polylactic acid (PLA) and scaled up to 100%, 200%, and 400% to be able to observe the velocity profiles of the mechanism more clearly. Experiments are performed with this prototype to compare the inlet and outlet mass flow rates at different configurations of the jaws. The particles used in these experiments are 0.3mm HSP 40/70 that are commonly used in particle-based CSP systems.

14 SOLAR ENERGY↗
DOE OSTI2023

DESIGNING A PARTICLE FLOW CONTROL APPARATUS

Flow control within a particle-based Concentrated Solar Power (CSP) system is essential in determining the heat transfer coefficient, and therefore, the power generation capability of these systems. There are three areas where particle flow control is significant: the receivers, storage tanks, and particle-sCO2 heat exchangers. The focus of this paper is on designing a new mechanism to control the flow in the particle-sCO2 heat exchangers due to the simplicity and potential cost savings when compared to the other areas of interest. The goal is for this new design to have quicker response times in terms of particle flowrate than a slide gate or flow control valve, which are designs currently used. The design resembles that of a chuck mechanism within a drill where a rotation of the sleeve elicits movement of the jaws both vertically and horizontally to close the outlet area of the nozzle. Additionally, this design will utilize the current actuator that is already used within these heat exchangers to reduce the complexity of implementation. The jaws are designed to be closed at an angle of 76 ̊ which is just slightly steeper than the hopper leading to the mechanism. Furthermore, this design can be tuned to limit particle bridging and other particle flow phenomena that result in blockages. The prototypes were 3D printed out of polylactic acid (PLA) and scaled up to 100%, 200%, and 400% to be able to observe the velocity profiles of the mechanism more clearly. Experiments are performed with this prototype to compare the inlet and outlet mass flow rates at different configurations of the jaws. The particles used in these experiments are 0.3mm HSP 40/70 that are commonly used in particle-based CSP systems.

14 SOLAR ENERGY↗
DOE OSTI2024

Metadynamics simulations reveal mechanisms of Na + and Ca 2+ transport in two open states of the channelrhodopsin chimera, C1C2

Cation conducting channelrhodopsins (ChRs) are a popular tool used in optogenetics to control the activity of excitable cells and tissues using light. ChRs with altered ion selectivity are in high demand for use in different cell types and for other specialized applications. However, a detailed mechanism of ion permeation in ChRs is not fully resolved. Here, we use complementary experimental and computational methods to uncover the mechanisms of cation transport and valence selectivity through the channelrhodopsin chimera, C1C2, in the high- and low-conducting open states. Electrophysiology measurements identified a single-residue substitution within the central gate, N297D, that increased Ca 2+ permeability vs. Na + by nearly two-fold at peak current, but less so at stationary current. We then developed molecular models of dimeric wild-type C1C2 and N297D mutant channels in both open states and calculated the PMF profiles for Na + and Ca 2+ permeation through each protein using well-tempered/multiple-walker metadynamics. Results of these studies agree well with experimental measurements and demonstrate that the pore entrance on the extracellular side differs from original predictions and is actually located in a gap between helices I and II. Cation transport occurs via a relay mechanism where cations are passed between flexible carboxylate sidechains lining the full length of the pore by sidechain swinging, like a monkey swinging on vines. In the mutant channel, residue D297 enhances Ca 2+ permeability by mediating the handoff between the central and cytosolic binding sites via direct coordination and sidechain swinging. We also found that altered cation binding affinities at both the extracellular entrance and central binding sites underly the distinct transport properties of the low-conducting open state. This work significantly advances our understanding of ion selectivity and permeation in cation channelrhodopsins and provides the insights needed for successful development of new ion-selective optogenetic tools.

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

Long-Term field testing of the accuracy and HVAC energy savings potential of occupancy presence sensors in A Single-Family home

The energy-saving potential of occupancy-centric smart thermostats has been extensively explored in simulations but lacked field testing for energy savings quantification and sensor performance assessment in real buildings. This paper presents a long-term field study conducted in a single-family home in Texas, U.S. to evaluate the performance of occupancy-centric controls (OCC) of HVAC (heating, ventilation, and air-conditioning) system in terms of energy savings, sensor accuracy, and impact on electric peak demand. The test site was equipped with a commercial off-the-shelf (COTS) smart thermostat and multiple occupancy presence sensors for OCC implementation. Additionally, a sub-metering system was installed to monitor electricity consumption of various end-use equipment, including the HVAC system. A supplementary device was installed to track the ground-truth occupancy for the accuracy evaluation of the occupancy presence sensor. Scenarios of baseline and OCC controls were alternated weekly over the 20-month testing period. The results indicated an effective OCC execution, as evidenced by indoor temperature profiles. During the 2023 cooling season, OCC achieved total energy savings of 1,958 kWh, corresponding to a 17.6% energy savings ratio. Under certain conditions, daily HVAC energy savings reached as high as 17 kWh, with a savings ratio of 35%. Sensor performance showed an overall accuracy of 83.8%, a False Positive Rate (FPR) of 12.8%, and a False Negative Rate (FNR) of 47.4%. A key limitation was the sensor’s inability to detect stationary occupants during sleep, leading to a midnight FNR of nearly 100% and significantly compromising thermal comfort. Additionally, the implementation of OCC resulted in extended periods of high electricity demand on summer afternoons, affecting occupant’s thermal comfort and posing potential challenges to community-level grid operations if OCC were widely adopted. Furthermore, this study addresses a critical research gap by empirically investigating energy-saving potential and occupancy sensor performance in residential buildings. Through a comprehensive field-testing study, the research examines the interrelationship between sensor accuracy, energy savings, and thermal comfort, an area that has received limited attention in the current literature.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Coherent homodyne detection for amplified cross-beam electric-field induced second harmonic

The electric-field induced second harmonic (E-FISH) signal sensing is commonly used as a nonlinear optical technique to probe electric fields inside a plasma region. Cross-beam E-FISH is being investigated to improve spatial resolution by defining the interaction volume via a controlled geometry of two overlapping noncolinear optical beams. This drastic reduction in interaction length of the electric field and laser region results in a significant signal reduction. Here, to overcome this signal reduction, we introduce coherent amplification of the cross-beam E-FISH signal by mixing the low E-FISH signal with a phase-locked bright local oscillator. We demonstrate enhancement of the signal. By introducing a local oscillator we can now derive the polarity of the measured electric field through the phase of the homodyne signal. To illustrate the technique, we, for the first time, to the best of our knowledge, measure the magnitude and the direction of the electric field in a cold atmospheric pressure plasma jet, which dynamically follows the profile of the applied bias current.

42 ENGINEERING↗
DOE OSTI2020

Fabrication of Freestanding Metallic Ni-Mo-W Microcantilever Beams With High Dimensional Stability

Recent studies have elucidated a promising balance of physical and mechanical properties of sputter deposited nickel-molybdenum-tungsten (Ni-Mo-W) films that have a unique nanotwinned microstructure and promising potential for use in high temperature microelectromechanical systems (MEMS). Here, the current study was undertaken to establish the feasibility of making nanotwinned Ni-Mo-W microcantilevers with standard micro- fabrication processing, to assess their dimensional stability, and to demonstrate the possibility of using nanotwinned Ni-Mo-W in metal MEMS devices. Deposition of Ni-Mo-W films in commercial sputtering chambers revealed a wide processing window for the formation of the requisite nanotwinned microstructure. Conventional photolithography and etchants were employed to shape blanket Ni-Mo-W films into freestanding microcantilever beams. Monitoring microcantilever deflections via interferometry provided a direct measure of residual stresses and overall dimensional stability. Heat treatments of 200° C and 400° C were used to mimic wafer bonding temperatures. At 400°C, microcantilevers exhibited modest stress relaxation, yielding beam deflection profiles on the nanometer scale and portending dimensional stability and control for future metal MEMS devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effects of temperature inversion on densification in chemical vapor infiltration

In a classical chemical vapor infiltration (CVI) process, the competing effects of chemical kinetics and reagent gas transport lead to non–uniform depositions such that outer layers of a preform densify faster leaving the core highly porous. Currently, CVI must be performed at a sufficiently low temperature to achieve good densification quality which leads to high processing time and cost. Volumetric heating of the preform, especially through microwaves, can create temperature inversion such that the core is hotter than the outer surface and potentially, overcome the challenges associated with isothermal CVI. Direct numerical simulations (DNS) of densification under various such temperature distributions indicate that microwave heating in CVI processing can lead to better (uniform) densification of porous preforms. Here the role of key parameters describing the temperature distributions on the densification behavior is investigated. Strategic temporal control of the temperature distribution shows that processing times can be reduced by almost half while maintaining a good densification quality similar to that of low–temperature isothermal processing. Inside–out densification due to the inverted temperature profile is a key distinguishing characteristic of microwave assisted CVI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. More accurate simulations with fast electron diffusion are even slower, requiring multiple hours of run time with parallel processing. The machine learning models use a database of 16,000+ GEN-RAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods implemented in πScope ensure that the database covers the range of 9 input parameters (n e0 , T e0 , I p , B t , R 0 , n ∥︀ , Z e f f , V loop , P LHCD ) with sufficient density in all regions of parameter space. The surrogate models reduce the computation time from minutes-hours to ms with high accuracy across the input parameter space. Data-driven surrogate models also allow for solving inverse and “lateral” problems. A surrogate model for the inverse problem maps from a desired current drive or power deposition profile to a set of input parameters that would result in such a profile, while a surrogate model for the lateral problem maps from a measured experimental quantity such as hard x-ray emission to a current drive or power deposition profile. In conclusion, the πScope database creation workflow is flexible and applicable to other RF simulation codes such as TORIC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗