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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Mechanical Properties of Aged A709

A709 plate is in the process of being developed and qualified through a collaboration by Argonne National Laboratory (ANL), Idaho National Laboratory (INL), and Oak Ridge National Laboratory (ORNL). The goal is to qualify A709 plate in Section III, Division 5 of the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC). This would permit the construction of A709 plate for fast-reactor structural applications. A tradeoff between creep and creep-fatigue properties was established in prior work. A processing route was identified as providing the optimal balance between creep-rupture and elevated-temperature cyclic properties for the solution annealed condition. This condition, however, resulted in a shorter than desired creep-rupture life. Aging is probed to evaluate its potential at further improving mechanical properties. Aging statically precipitates the solutes in solution prior to service. The processing routes identified as providing the best creep-rupture properties and best balance in mechanical properties are investigated. This report discloses the results from tensile, creep, and elevated-temperature cyclic testing performed at INL on the aged material. The aged properties are compared to solution annealed properties. A709 offers improvement in performance compared to 316H particularly at high temperatures; 316H is a material qualified in Section III, Division 5 of the ASME BPVC. For certain high-temperature fast-reactor design conditions, 316H cannot be used while A709 can.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Optical properties of bimetallic Au-Cu nanocrystals embedded in glass

Highlights: • Bimetallic Au-Cu/Au-Cu sosoloid nanocrystals embedded in glass have been synthesized. • We achieved good size control of the nanocrystals. • The glasses with bimetallic nanoparticles exhibit enhanced for NLO. • The mechanisms on the nonlinear effects of the obtained glasses are discussed. - Abstract: Bimetallic gold-copper and gold-copper solid solutions nanocrystals (NCs) with orthorhombic morphologies were successfully embedded in sodium borosilicate glass; these materials were fabricated via a facile and synthetic sol-gel technique. Microstructural investigations demonstrate that the Au-Cu intermetallic nanostructure is generated in the glass host. Z-scan technique was applied to reveal the third-order nonlinear optical properties of the as-obtained glasses at the wavelength of 800 nm. The as-synthesized glasses exhibit similar nonlinear behaviors with reverse saturation absorption effects and self-focusing performances. The third-order nonlinear susceptibility χ{sup (3)} values were optimized by tuning the sizes of the Au-Cu NCs. The χ{sup (3)} of Au-Cu(1), Au-Cu(2) and Au-Cu(3) measured to be 3.1 × 10{sup −12}, 5.4 × 10{sup −12}, and 4.4 × 10{sup −12} esu for the single-pulse energy of 1 μJ. We have discussed the nonlinear optical mechanism of Au-Cu sodium borosilicate glass that may be due to the quantum confinement effects and surface plasmon resonance effects.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Improving the bioaccessibility of lipophilic ingredient in its oral intestinal delivery by ultrasound and biological cross‐linker

Abstract BACKGROUND Great efforts have been made to improve the oral bioaccessibility of lipophilic ingredients with multi‐functionalities. Achieving intestinal delivery of lipophilic ingredients and their encapsulation in micelles composed of bile salts and lipid hydrolysates (i.e. fatty acids) is critical for improving oral bioaccessibility. Therefore, oil‐core microcapsules are considered ideal carriers of lipophilic ingredients. Previous studies have reported oil‐core/zein‐shell microcapsules constructed by a one‐step anti‐solvent process. Still, its efficacy as an intestinal delivery system was limited because if the porous shell structure. RESULTS Zein solution was pretreated with ultrasound and tannic acid (TA) cross‐linking. Composite oil‐core microcapsule (COM) with a compact shell structure was successfully prepared by using modified zein solution in the anti‐solvent process. Fourier‐transform infrared spectroscopy and circular dichroism analyses indicated that ultrasound and TA synergistically promote the conformational transition of zein from α‐helix to β‐sheet and enhance the hydrophobic interactions among protein chains. The above changes contribute to the strengthen of shell zein network. Correspondingly, COM presents superior encapsulation efficiency and environmental stability over the simple oil‐core microcapsule (SOM) prepared without the use of ultrasound and TA. Furthermore, antioxidant activity of β‐carotene was well retained during the encapsulation process. In vitro studies indicated that COM was more resistant to digestibility and acid‐induced swelling. More than 87% of β‐carotene could be released in the intestine in a sustainable way. The controllable release behavior thus promoted a significant increase in bioaccessibility of β‐carotene encapsulated in COM compared to SOM (85.9% versus 48.5%). CONCLUSION The COM generated here shows potential for bioaccessibility improvement of lipophilic ingredients. © 2022 Society of Chemical Industry.

Wei, Yun‐Shan↗
DOE OSTI2019

An Eco-friendly Porous Poly(imide-ether)s for the Efficient Removal of Methylene Blue: Adsorption Kinetics, Isotherm, Thermodynamics and Reuse Performances

Poly(imide-ether)s (PIEs), which is porous in nature, was synthesized using aromatic diamines and dianhydrides via the solution polycondenzation reaction. In the process, PIEs was used as an adsorbent for the removal of basic dye [Methylene blue (MB)] from the aqueous solution. The structure and the thermal stability of PIEs were characterized by FT-IR, {sup 1}H-NMR, XRD and TG analysis, and the adsorption behaviour of the PIEs was confirmed using UV/Visible, FT-IR and SEM with EDX analysis. Batch adsorption experiments were carried out and their parameters (pH 6.95), initial MB concentration (200 mg/L), adsorbent dosage (50 mg), contact time (120 min) and temperature (28 °C) were optimized. The batch adsorption experimental data of the effect of contact time, initial MB concentration and temperature were evaluated using the adsorption kinetics (Pseudo-first order, Pseudo-second order, Elovich and Intra-particle diffusion kinetic), isotherm (Langmuir, Freundlich, Redlich–Peterson and Sips isotherms) and thermodynamic models respectively. In the study, adsorption of MB onto PIEs followed Pseudo-second kinetics and found to be the best fitting model based on the obtained experimental data. The homogeneity and heterogeneity surface nature of PIEs were elucidated with two and three isotherm parameters respectively. The adsorption thermodynamic study indicates that the adsorption of MB onto PIEs was endothermic and spontaneous in nature. The adsorbed PIEs solid waste was utilized to prepare the polymer composite, and its property was characterized. Graphical Abstract: .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

Finding actionable trends in laser-based metal additive manufacturing process monitoring data is challenging owing to the diversity and complexity of the underlying physical interactions. A single monitoring solution that captures a particular process phenomenon, such as a photodiode that tracks melt pool intensity, is not alone capable of evaluating process stability or detecting flaw formation with sufficient precision for routine application in industry. In this work, to improve flaw detection performance, we adopted a data fusion approach that captures multiple process phenomena. To demonstrate this, we acquired data from laser powder bed fusion (LPBF) builds of cylindrical specimens produced with different laser spot sizes, emulating defocusing due to process faults such as thermal lensing. The resulting specimens had porosity of varying types and severity, quantified by post-build non-destructive X-ray computed tomography, Archimedes density measurements, and destructive metallographic characterization. During the build, the melt pool state was monitored with two coaxial high-speed video cameras and a temperature field imaging system. Physically intuitive low-level melt pool signatures, such as melt pool temperature, shape and size, and spatter intensity were extracted from this high-dimensional, image-based sensor data. These process signatures were subsequently used as input features in relatively simple machine learning models, such as a support vector machine, which were trained to detect laser defocusing, and in addition, predict porosity type and severity. The results show that the data fusion approach significantly enhanced system performance by reducing the overall false positive rate from ~ 0.1 to ~ 0.001 without sacrificing the true positive rate (~0.90). These results were at par with a black-box, deep machine learning approach (convolutional neural network).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effect of CMAS viscosity on the infiltration depth in thermal barrier coatings of different microstructures

Calcium magnesium aluminum silicate (CMAS) is one of the leading concerns for the gas turbine industry. The effects of CMAS viscosity and the coating microstructure on CMAS infiltration depth were explored by conducting a time dependent interaction study. Three CMAS compositions were used from literature, and their viscosities predicted through FactSage viscosity module were drastically different. The interaction was carried out on three different TBCs synthesized using the solution precursor plasma spray process (SPPS): two of the TBCs were made of yttrium aluminum garnet (YAG) having different microstructures that promote different modes of CMAS infiltration, and one TBC was made of gadolinium zirconate (GZO). All samples had stress relieving vertical cracks and different intensities of horizontally banded porosity, (inter pass boundaries IPBs). A concentration of 100 mg/cm 2 of CMAS was applied on the TBCs which were then subjected to a 5-minute interaction at 1300 °C. Samples were analyzed using scanning electron microscopy (SEM), electron dispersive X-ray spectroscopy (EDXS), and transmission electron microscopy (TEM). Low viscosity CMAS readily penetrated the TBCs while more viscous CMAS showed less penetration. The depth of CMAS infiltration depended on the coating microstructure. In the YAG with IPBs, the CMAS spread horizontally in the IPBs before infiltrating deeper, resulting in reduced infiltration depth compared to other samples in spite of having wider vertical cracks. TEM and EDXS analysis were performed to investigate the phases present in the CMAS-TBC interaction region in YAG. Two regions were chosen, the top TBC surface in direct contact with the sea of CMAS, and the region at the CMAS penetration ended within the coating. Finally, the results showed that no secondary phases like apatite were observed in YAG, thus it can be concluded that the arrest of CMAS happened solely because of CMAS viscosity and the short infiltration time.

36 MATERIALS SCIENCE↗
NASA NTRS2000

A Parallel Genetic Algorithm for Automated Electronic Circuit Design

Parallelized versions of genetic algorithms (GAs) are popular primarily for three reasons: the GA is an inherently parallel algorithm, typical GA applications are very compute intensive, and powerful computing platforms, especially Beowulf-style computing clusters, are becoming more affordable and easier to implement. In addition, the low communication bandwidth required allows the use of inexpensive networking hardware such as standard office ethernet. In this paper we describe a parallel GA and its use in automated high-level circuit design. Genetic algorithms are a type of trial-and-error search technique that are guided by principles of Darwinian evolution. Just as the genetic material of two living organisms can intermix to produce offspring that are better adapted to their environment, GAs expose genetic material, frequently strings of 1s and Os, to the forces of artificial evolution: selection, mutation, recombination, etc. GAs start with a pool of randomly-generated candidate solutions which are then tested and scored with respect to their utility. Solutions are then bred by probabilistically selecting high quality parents and recombining their genetic representations to produce offspring solutions. Offspring are typically subjected to a small amount of random mutation. After a pool of offspring is produced, this process iterates until a satisfactory solution is found or an iteration limit is reached. Genetic algorithms have been applied to a wide variety of problems in many fields, including chemistry, biology, and many engineering disciplines. There are many styles of parallelism used in implementing parallel GAs. One such method is called the master-slave or processor farm approach. In this technique, slave nodes are used solely to compute fitness evaluations (the most time consuming part). The master processor collects fitness scores from the nodes and performs the genetic operators (selection, reproduction, variation, etc.). Because of dependency issues in the GA, it is possible to have idle processors. However, as long as the load at each processing node is similar, the processors are kept busy nearly all of the time. In applying GAs to circuit design, a suitable genetic representation 'is that of a circuit-construction program. We discuss one such circuit-construction programming language and show how evolution can generate useful analog circuit designs. This language has the desirable property that virtually all sets of combinations of primitives result in valid circuit graphs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. Using a parallel genetic algorithm and circuit simulation software, we present experimental results as applied to three analog filter and two amplifier design tasks. For example, a figure shows an 85 dB amplifier design evolved by our system, and another figure shows the performance of that circuit (gain and frequency response). In all tasks, our system is able to generate circuits that achieve the target specifications.

Long, Jason D.↗
DOE OSTI2024

Direct Air Capture of CO 2 via Reactive Crystallization

Atmospheric CO 2 removal using engineered chemical processes, aka direct air capture (DAC), has become an essential component of our available portfolio for mitigating climate change. Here we describe a promising approach to DAC based on reactive crystallization of atmospheric CO 2 (RC-DAC) with aqueous guanidine and amino acid. Compared to the previously studied phase-changing DAC processes involving initial CO 2 absorption by an aqueous alkaline solvent followed by carbonate crystallization in a second step, RC-DAC combines the CO 2 absorption and carbonate crystallization into a single step. Thus, as the insoluble carbonate salts are removed from solution by crystallization, more CO 2 is pulled from the air into solution, further driving the DAC process. The RC-DAC was performed in a household humidifier as the air–liquid contactor, which can handle solid–liquid slurries effectively. The crystallization was monitored in situ by pH measurements, real-time imaging with a microscope probe, and by Raman spectroscopy, and ex situ by NMR spectroscopy, powder X-ray diffraction, and total inorganic carbonate analysis. Further, the investigation provided a detailed mechanistic picture of the RC-DAC process, involving formation of carbamate and carbonate anions in solution, followed by sequential crystallization of different guanidinium carbonate phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

EReinit: Scalable and efficient fault-tolerance for bulk-synchronous MPI applications

Scientists from many different fields have been developing Bulk-Synchronous MPI applications to simulate and study a wide variety of scientific phenomena. Since failure rates are expected to increase in larger-scale future HPC systems, providing efficient fault-tolerance mechanisms for this class of applications is paramount. The global-restart model has been proposed to decrease the time of failure recovery in Bulk-Synchronous applications by allowing a fast reinitialization of MPI. However, the current implementations of this model have several drawbacks: they lack efficiency; their scalability have not been shown; and they require the use of the MPI profiling interface, which precludes the use of tools. Here, we present EReinit, an implementation of the global-restart model that addresses these problems. Our key idea and optimization is the co-design of basic fault-tolerance mechanisms such as failure detection, notification, and recovery between MPI and the resource manager in contrast to current approaches on which these mechanisms are implemented in MPI only. We demonstrate EReinit in three HPC programs and show that it is up to four times more efficient than existing solutions at 4,096 processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Continuous-Time Public Good Contribution Under Uncertainty: A Stochastic Control Approach

In this paper we study continuous-time stochastic control problems with both monotone and classical controls motivated by the so-called public good contribution problem. That is the problem of n economic agents aiming to maximize their expected utility allocating initial wealth over a given time period between private consumption and irreversible contributions to increase the level of some public good. We investigate the corresponding social planner problem and the case of strategic interaction between the agents, i.e. the public good contribution game. We show existence and uniqueness of the social planner’s optimal policy, we characterize it by necessary and sufficient stochastic Kuhn–Tucker conditions and we provide its expression in terms of the unique optional solution of a stochastic backward equation. Similar stochastic first order conditions prove to be very useful for studying any Nash equilibria of the public good contribution game. In the symmetric case they allow us to prove (qualitative) uniqueness of the Nash equilibrium, which we again construct as the unique optional solution of a stochastic backward equation. We finally also provide a detailed analysis of the so-called free rider effect.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Characterizing Reactive Transport Behavior in a Three-Dimensional Discrete Fracture Network

While several studies have linked network and in-fracture scale properties to conservative transport behavior in subsurface fractured media, studies on reactive transport cases remain relatively underdeveloped. In this study, we explore the behavior of an irreversible kinetic reaction during the interaction of two solute plumes, one consisting of species A and the other species B. When the plumes converge, these species react kinetically to form a new species C via A+B→kC. This reactive system is studied using a three-dimensional discrete fracture network (DFN) model coupled with reactive Lagrangian particle tracking. We find that the interplay of network topology and chemical properties of the reactive solutes controls reactive transport processes. The network topology drives species A and B together, and the chemical properties dictate whether and how quickly a reaction occurs. Results demonstrate that reactions are most likely to occur in high-velocity fractures that make up the network backbone. The interplay between species’ chemical properties and transport is characterized by a non-dimensional Damköhler (Da) number. We show that the spatial distribution of reactions is sensitive to Da, which subsequently influences late-time tailing behavior in outlet breakthrough time distributions. The results of this study provide initial insights into how an irreversible reaction occurs during transport in a fracture network, using a methodology that can be applied to study reactive transport in a wide range of fractured media environments and contexts.

58 GEOSCIENCES↗
DOE OSTI2018

Mathematical Modeling of Decarburization in Levitated Fe-Cr-C Droplets

Using carbon dioxide to replace oxygen as an alternative oxidant gas has proven to be a viable solution in the decarburization process, with potential for industrial applications. In a recent study, the transport phenomena governing the carbon dioxide decarburization process through the use of electromagnetic levitation (EML) was examined. CO{sub 2}/CO mass transfer was found to be the principal reaction rate control step, as a result gas diffusion has gained significant attention. In the present study, gas diffusion during decarburization process was investigated using computational fluid dynamics (CFD) modeling coupled with chemical reactions. The resulting model was verified through experimental data in a published paper, and employed to provide insights on phenomena typically unobservable through experiments. Based on the results, a new correction of the Frössling equation was presented which better represents the mass transfer phenomena at the metal-gas interface within the range of this research.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Binary Alkali Nitrate and Chloride Phase Diagrams: NaNO{sub 3}-KNO{sub 3}, LiNO{sub 3}-NaNO{sub 3}, LiNO{sub 3}-KNO{sub 3}, and NaCl-KCl

LiNO{sub 3}-NaNO{sub 3}, LiNO{sub 3}-KNO{sub 3,} NaNO{sub 3}-KNO{sub 3}, and NaCl-KCl phase relations were formulated using the regular solution model to obtain desired compositions for their potential application as a heat transfer fluid. The simultaneous nonlinear equations formed were solved numerically using a contour plot technique in Matlab. An algorithm was developed to determine the real roots of the coupled nonlinear equations and subsequent phase diagrams were constructed. The phase diagrams were compared with those predicted using FactSage thermochemical package and literature data from experimental studies. The calculated NaNO{sub 3}-KNO{sub 3} phase diagram shows that this system has a eutectic point at 0.5 mole fraction of KNO{sub 3} with a eutectic temperature of 220.85 °C, while the LiNO{sub 3}-KNO{sub 3} system was found to have a eutectic point at 0.44 mole fraction LiNO{sub 3} at 137 °C. The LiNO{sub 3}-NaNO{sub 3} system shows a eutectic at 0.524 mole fraction LiNO{sub 3} at 192.8 °C, and finally the NaCl-KCl system has a eutectic point at 0.48 mole fraction NaCl at 634 °C. The liquidus and solidus curves obtained fitted close against values obtained from the quasi-chemical model used in FactSage and experimental values from the literature. This study showed that the regular solution model combined with the contour plots approach can sufficiently describe the liquidus–solidus curves of the alkali binary nitrate and chloride systems and could be a useful method for predicting the phase diagrams for higher order alkali nitrates and chlorides.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Convergence and asymptotical stability of numerical solutions for neutral stochastic delay differential equations driven by G-Brownian motion

There are few numerical analysis results for nonlinear neutral stochastic delay differential equations driven by G-Brownian motion (G-NSDDEs). This paper is concerned with the numerical solutions of the G-NSDDEs to fill this gap. In this paper, we first devote to show that the stochastic theta numerical solution converges to the exact solution for the G-NSDDE. We then prove that the backward Euler–Maruyama numerical solution for the G-NSDDE is asymptotically mean-square stable under suitable conditions. Moreover, a numerical example is demonstrated to illustrate the effectiveness of our obtained results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Effects of ternary alloy additions on the microstructure of highly immiscible Cu alloys subjected to severe plastic deformation: An evaluation of the effective temperature model

Phase evolution in dilute, strongly immiscible Cu-Mo, Cu-Mo-Ni, and Cu-Mo-Ag alloys during severe plastic deformation at low-temperature has been experimentally investigated. For the Cu95Mo05 alloy, Mo nanoparticles are formed, ~10 nm in diameter, as part of a steady state microstructure, with less than ~1 at.% Mo dissolved in the matrix. Addition of 10 or 20 at.% Ni to this binary alloy results in a significant increase in the Mo solubility, whereas comparable additions of Ag has a corresponding little effect. The steady state microstructures of alloys during ball milling of elemental powders are very similar to those during HPT processing of initially homogeneous solutions. The results are discussed in terms of an effective temperature model. Model MD simulations are presented to help relate the predictions of the effective temperature model to atomistic mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Evaluation of human platelet lysate and dimethyl sulfoxide as cryoprotectants for the cryopreservation of human adipose-derived stem cells

Cryopreservation provides an effective technique to maintain the functional properties of human adipose-derived stem cells (ASCs). Dimethylsulfoxide (DMSO) and fetal bovine serum (FBS) are frequently used as cryoprotectants for this purpose. However, the use of DMSO can result in adverse effects and toxic reactions and FBS can introduce risks of viral, prion, zoonose contaminations and evoke immune responses after injection. It is therefore crucial to reduce DMSO concentrations and use serum-free solution in the cryopreservation process. Human platelet lysate (PL) is a promising candidate for use as an alternative to DMSO and FBS. Therefore, in this study, with an aim to identify a cryoprotective agent for ASC cryopreservation, we determined the viability, proliferation potential, phenotype, and differentiation potential of fresh ASCs and ASCs cryopreserved using different combinations of three cryoprotective agents: fetal bovine serum (FBS), dimethylsulfoxide (DMSO), and human platelet lysate (PL). The viability of the ASCs cryopreserved with 90% FBS and 10% DMSO, 95% FBS and 5% DMSO, and 97% PL and 3% DMSO was >80%, and the proliferation potentials, cell phenotypes, and differentiation potentials of these groups were similar to those of fresh ASCs. Together, our findings suggest that a combination of 97% PL and 3% DMSO is an ideal cryoprotective agent for the efficient cryopreservation of human ASCs. - Highlights: • 95% FBS with 5% DMSO can cryopreserve ASCs efficiently. • 97% PL with 3% DMSO can cryopreserve ASCs efficiently. • PL can replace FBS as an ideal cryoprotective agent to cryopreserve ASCs. • PL can preserve ASC viability, proliferation, phenotype, and differentiation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Impact of coolant temperature on the combustion characteristics and emissions of a stratified-charge direct-injection spark-ignition engine fueled with E30

The direct injection spark ignition (DISI) engine has received considerable attention due to its potential to increase the power density of traditional spark ignition engines while significantly improving fuel economy through lean, unthrottled combustion. However, the market introduction of DISI engines operated in a lean combustion mode is inhibited by their unsatisfactory emissions, especially during cold start conditions that make proper mixture formation more challenging. Ethanol-blended gasoline, now a widely used fuel, makes the cold start of a DISI engine more difficult, leading to higher HC and soot emissions because of the high latent heat of vaporization of ethanol relative to gasoline. This work investigated the impact of coolant temperature on the characteristics of combustion and emissions in a stratified-charge DISI engine fueled with an E30 fuel (i.e. 30% ethanol in gasoline), while the coolant temperature was alternated between four levels (45, 60, 75, and 90 °C) to simulate different conditions throughout the warm-up process. The experiments showed that the coolant temperature affected the post-spark inflammation time, as well as the speed, intensity, and stability of the combustion process in the engine. When the coolant temperature rose, the engine produced more NOX and less CO, PM and HC. In addition, high-speed direct photography was used to obtain crank-angle resolved images of fuel sprays and flames in the cylinder. As the coolant temperature rose, the liquid spray lengths became shorter, reducing the possibility of wall wetting, and reduced irradiance from soot particles also indicated less nonpremixed combustion. The in-cylinder imaging results are consistent with the observed combustion and emission characteristics and shed light on the underlying processes. Finally, some potential solutions to the emissions challenges faced here could be either raising in-cylinder temperatures by using trapped residuals or modifying the injection schedule, for example by increasing the number of injections or to inject later in the cycle into a higher-density environment.

42 ENGINEERING↗
DOE OSTI2021

Explicit physics-informed neural networks for nonlinear closure: The case of transport in tissues

In upscaling methods, closures for nonlinear problems present a well-known challenge. While a number of theoretical methods have been proposed for handling such closures, nonlinearities still remain a significant obstacle for many problems. In this work, we use a combination of formal upscaling and data-driven machine learning for explicitly closing a nonlinear transport and reaction process in multiscale tissues. The classical effectiveness factor model is used to formulate the macroscale reaction kinetics. We train a multilayer perceptron network using training data generated by direct numerical simulations over microscale examples. Once trained, the network is used in an algorithm for numerically solving the upscaled (coarse-grained) differential equation describing mass transport and reaction in two example tissues. The network is described as being explicit in the sense that the network is trained using macroscale concentrations and gradients of concentration as components of the feature space rather than incorporating them as part of a constraint in the optimization process. Network training and solutions to the macroscale transport equations were computed for two different tissues. The two tissue types (brain and liver) exhibit markedly different geometrical complexity and spatial scale (cell size and sample size). The upscaled solutions for the average concentration are compared with numerical solutions derived from the microscale concentration fields by a posteriori averaging. There are three outcomes of this work of particular note. 1) Our overall approach results in an upscaled nonlinear PDE. The PDE is closed using a neural network, and our approach results in the definition of the classical effectiveness factor for effecting closure. 2) We identify particular source terms for the closure problem that are important for representing the structure of the closure. These source terms involve macroscale concentrations and their gradients. We adopt these source terms to use as explicit features in the learning algorithm. We find the trained networks that include the macroscale source terms generate models that are able to predict the correction factor with increased fidelity over those that do not. 3) We find that the trained network exhibits good generalizability, and it is able to predict the effectiveness factor with high fidelity for realistically-structured tissues despite the significantly different scale and geometrical complexity of the two example tissue types. This latter result emphasizes our purposeful connection between conventional averaging methods with the use of machine learning for closure; this contrasts with some machine learning methods for upscaling where the exact form of the macroscale equation remains unknown.

97 MATHEMATICS AND COMPUTING↗