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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Enhancement of phase change material hysteresis model: A case study of modeling building envelope in EnergyPlus

Nowadays, buildings are expected to offer demand side services to the power grid to enhance the electrical load flexibility, which leads to the concepts of grid-interactive efficient buildings (GEBs). Phase change material (PCM)-based thermal energy storage has seen increasing attention in recent years for peak load shifting of grid-interactive efficient buildings (GEBs). Numerical models are critical tools for design and evaluation of PCM-integrated systems. Most industrial-grade PCMs are reported to melt/freeze over a temperature range instead of at a unique temperature. Such thermal hysteresis effect significantly affects the reliability of simulation results because not only the heat transfer process depends on melting and freezing temperatures, the PCM thermal properties change significantly during the phase change process as well. This study is aimed to develop a model for the PCMs used in the building envelope with the capability to accurately simulate hysteretic behaviors. Further, this model is based on a two-phase assumption and is implemented in a whole building energy performance simulation program (i.e., EnergyPlus). A comparison between numerical results and experimental data shows that during a complete phase transition, the two-phase model could achieve a good agreement with the experimental data. During a partial phase transition, the two-phase model could lead to significant improvements compared to other alternative PCM models, including the existing PCM model in EnergyPlus. Last, whole building simulations were performed to study this model's performance regarding heating/cooling loads and zone mean air temperature of a given building. The results show that the difference in hourly heating/cooling loads introduced by the models was less than 1% in design conditions, while significant changes were observed in both hourly heating/cooling loads and zone mean air temperature when the PCM envelope underwent partial phase transition processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Mexico and U.S. Power Systems Under Variations in Natural Gas Prices

This study examines the impact of natural gas prices on the power systems of Mexico and the United States. For this, we develop an integrated modeling framework by soft linking three different techno-economic bottom-up models of the power and energy systems, one partial equilibrium model of the natural gas sector, and a partial equilibrium model of the Mexican energy sector. Our results show several interesting results: high natural gas prices raise the use of carbon-intensive technologies in the short-term and boost renewable investments at longer time intervals, increasing emissions in earlier periods and reducing them thereafter. Regarding system costs, because of more capital-intensive green power and lower expenditures in raw energy carriers, capital costs rise and operating costs decrease in the long haul. Furthermore, we see an increase in natural gas demand when its price is low, reducing long-term capital and operating costs through cheaper energy inputs in natural gas facilities and a lower share of capital-intensive renewable facilities in the power system. Concerning emissions, low natural-gas prices decrease coal use in the United States, reducing anthropogenic emissions until the last stages of the optimization period. For Mexico, they show heterogeneous results across models. Policymakers can use this study's results to understand the influence of natural gas prices in the Mexican and United States energy sectors.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Combustion dynamics of crude and upgraded Thermal DeOxygenation oils in a compression ignition engine

Thermal DeOxygenation (TDO) is a robust thermochemical conversion scheme to produce hydrocarbons from biomass feedstock. The process targets the carbohydrate fraction of biomass to yield a broad mixture of primarily aromatic hydrocarbons within a boiling point range of 348–798 K with low oxygen content (<4 wt%). The resulting materials are amenable to traditional hydrotreating and distillation processes with approximately 70% by mass in the distillate fuel range. The simple conversion scheme combined with commercially viable upgrading routes makes TDO oils a feasible alternative fuel for transportation applications. Here this paper is the first systematic treatment of fit-for-purpose testing of TDO oils in a compression ignition engine. Blends of partially upgraded TDO oils (e.g. whole oil, distilled oil, hydrotreated oil and hydrotreated-distilled oil) are prepared with certified ultra-low sulfur diesel at 5%, 10%, 15% and 20% by volume. The resulting fuels are analyzed for fuel characteristics and combustion dynamics in an instrumented single-cylinder compression ignition engine. All fuel blends at 10% blend level by volume exhibited adequate engine performance. Hydrotreating of the oils is a necessary step to meet cetane number and EPA soot emissions requirements at 20% blend volume. Combined distillation and hydrotreatment meet or exceed all fuel specification and engine performance benchmarks. Partially upgraded TDO oils are suitable fuel options for compression ignition applications.

42 ENGINEERING↗
DOE OSTI2021

An Experimental Study of the Solubility of Rare Earth Chloride Salts (La, Nd, Er) in HCl Bearing Water Vapor from 350 – 425 °C

In this work, the solubilities of the rare earth chlorides REECl 3 , where REE = (La, Nd, Er), were measured in HCl bearing water vapor from 350 – 425°C with water partial pressures ranging from 8 – 170 bar. Solubility data were fit to the Pitzer-Pabalan quasi-chemical model in order to extract thermodynamic parameters for the formation of the gaseous REE-chloride-water clusters REECl 3 (H 2 O) n . The data show that the solubility of the REE chlorides are orders of magnitude higher than salts such as NaCl or CuCl at low water fugacities, despite their sublimation energies being substantially higher. This enhanced solubility is likely due to the high enthalpy associated with binding a single water molecule to form the species REECl 3 (H 2 O), with derived enthalpies ranging from –378 to –465 kJ/mol. Addition of further water molecules to form higher order clusters (n > 1) involves enthalpy changes of ~ -20 kJ/mol, and are in effect thermodynamically suppressed over the temperature range 350 – 425°C. Despite the enhanced solubility of small REECl 3 water clusters, simulations of boiling processes demonstrate that the REE show highly conservative behavior, partitioning strongly into the dense aqueous phase. Not surprisingly, the presence of phosphates in the system makes this effect even more pronounced, completely immobilizing the REE. This would reduce transport in both the vapor and aqueous phase to negligible levels. However, we suggest that vapor phase transport of the REE may play a significant role in systems having a relatively low partial pressure of water (below the saturation point), where the relatively high stability of the first hydrated REE chloride clusters (REECl 3 (H 2 O) and REECl 3 (H 2 O) 2 ) will give a preference for gas transport of the REE relative to other elements. This can likely happen in systems involving a gas/melt exchange in fumarolic exhalations, where water vapor discharges at relatively low (close to atmospheric) pressures.

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

The solubility of La hydroxide and stability of La 3+ and La hydroxyl complexes at acidic to mildly acidic pH from 25 to 250 °C

The mobility of rare earth elements (REE) in natural hydrothermal systems can be assessed using geochemical modeling, which requires reliable thermodynamic data of relevant aqueous species. In this study, we evaluate the controls of pH and temperature on La speciation and the role of hydroxyl complexes in REE transport at hydrothermal conditions. Batch-type hydrothermal solubility experiments were conducted using synthetic La hydroxide powders equilibrated in perchloric acid-based aqueous solutions at temperatures between 150 and 250 °C and starting pH of 2 to 5. The La hydroxide solubility is retrograde with temperature and displays a strong pH dependence with a decrease in La concentrations from acidic to mildly acidic pH spanning between 3 and 5 orders of magnitude (e.g. log La molality of –2.5 to –7.2 at 250 °C). Thermodynamic optimizations using GEMSFITS allow to retrieve the standard partial molal Gibbs energies for the La 3+ aqua ion and the formation constants for the La hydroxyl species (i.e., LaOH 2+ , La(OH) 2 + , La(OH) 3 0 ) between 25 and 250 °C. A comparison between the experimentally derived thermodynamic properties with the calculated values from the Helgeson-Kirkham-Flowers equation of state parameters indicates an increased divergence with temperature. Discrepancies in standard partial molal Gibbs energies range between ~ 1 – 12 kJ/mol and result in a predicted La hydroxide solubility differing by up to 3 orders of magnitude at 250 °C. Speciation calculations indicate a higher stability of La 3+ and LaOH 2+ over the other La hydroxyl species in the studied pH range of 3.4 to 6. Here, the optimized thermodynamic properties for La aqueous species have important implications for modeling the solubility of REE minerals such as monazite and the mobility of REE in hydrothermal systems.

58 GEOSCIENCES↗
DOE OSTI2025

Mineralogical and isotopic constraints on early, high-temperature events and reservoirs recorded in the interior of a Type B Ca-Al-rich inclusion from the reduced CV3 chondrite Vigarano

A coordinated mineralogical and oxygen and Al-Mg isotopic study of a Type B Ca-Al-rich inclusion (CAI) from the reduced CV3 chondrite Vigarano was carried out using electron microprobe analysis, transmission electron microscopy, and secondary ion mass spectrometry. This CAI, a once molten igneous object, shows heterogeneous oxygen isotopic compositions among its constituent mineral phases. Spinel is uniformly 16 O-rich with Δ 17 O ≤ −23 ‰. The Δ 17 O values of Al,Ti-diopside in the CAI core range from −11 ‰ to −18 ‰, which are positively correlated with its TiO 2 contents, whereas diopside in the Wark–Lovering (WL) rim is 16 O-rich with Δ 17 O = −23 ‰. Melilite in the CAI mantle shows Δ 17 O values ≤ −10 ‰ only when Åk <15 but becomes more 16 O-poor (Δ 17 O = −3 ‰ to −9 ‰) when Åk >15 . These correlated chemical and oxygen isotopic variations were likely established during crystallization of melilite and Al,Ti-diopside from a partial melt, while spinel preserves the original 16 O-rich composition of the CAI precursor. We infer that a partial melt was isotopically evolving from 16 O-rich to 16 O-poor during melilite crystallization, then back to 16 O-rich during Al,Ti-diopside crystallization via exchange with different gas reservoirs of 16 O-poor and 16 O-rich compositions during heating event(s). Our Al-Mg isotopic measurements of the CAI core and mantle define a single isochron with an inferred initial 26 Al/ 27 Al ratio of (4.93 ± 0.18) × 10 −5 , indistinguishable from that of the WL rim. This indicates that multiple high-temperature events and oxygen isotope exchange with isotopically distinct gas reservoirs occurred rapidly during the CAI formation.

Al-Mg isotopic systematic↗
DOE OSTI2023

Multi-omics of NET formation and correlations with CNDP1, PSPB, and L-cystine levels in severe and mild COVID-19 infections

We report that we performed a multi-omics analysis of an immunologically naïve SARS-CoV-2 clinical cohort to characterize overall changes in plasma among control (uninfected), mild, and severe infections. A comparison of healthy controls and patient samples showed activation of neutrophil degranulation pathways. Consistent with this observation, we characterized neutrophil extracellular trap (NET) complexes that were partially initiated in a subset of the mild infections (showing partially formed NETs) and fully-formed NETs in a subset of severe infections (containing multiple NET proteins in individual patient samples). As a potential mechanism to suppress NET formation, multiple redox enzymes were elevated in the mild and severe population. Analysis of metabolites from the same cohort showed a 24 and 60-fold elevation in plasma L-cystine, the oxidized form of cysteine and substrate of the powerful antioxidant glutathione in mild and severe patients, respectively. Unique to patients with mild infections, the carnosine dipeptidase modifying enzyme (CNDP1) was up-regulated. The strong protein and metabolite oxidation signatures suggest multiple compensatory pathways working to suppress both free radical and NET formation in SARS-CoV-2 infections.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Beta-Amino Carboxylate (BAC) non-aqueous physical solvents for enhanced CO2 separations in pre-combustion carbon capture, industrial CO 2 capture, and biogas upgrading processes

Novel beta-amino carboxylate (BAC) solvents have been synthesized and tested to efficiently capture carbon dioxide (CO 2 ) from process gas streams with CO 2 partial pressure intermediate between pre-combustion and post-combustion capture. The BAC solvents have molecular structures characterized by alkyl-substituted amides or esters containing a secondary amine functional group on the second carbon from the carbonyl carbon (referred to as the beta “β” carbon). The ester or amide functional group combined with optimal steric crowding around the amine nitrogen by proximate alkyl groups are tailored to modify the strength of CO 2 binding in the solvent. The solvents possess high CO 2 solubilities and high gas selectivity including good CO 2 /H 2 O selectivity and can be utilized for CO 2 absorption over a range of partial pressures. Due to low volatility, many of the solvents can be operated at or above ambient temperature which eliminates solvent chilling and allows regeneration using low grade waste heat. These novel solvents offer an opportunity for efficient carbon capture for a range of applications including biogas upgrading, hydrogen production, and pre-combustion carbon capture.

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

Interaction of extended dislocations with nanovoid clusters

Voids of nanoscale dimensions in irradiated metals can act as obstacles to dislocation motion and cause strengthening. In this work, nanovoid strengthening and the influences of void size, void spacing and material properties, such as stacking fault energies, on dislocation bypass mechanisms are investigated using Phase Field Dislocation Dynamics, a three-dimensional mesoscale model that predicts the minimum energy pathway taken by discrete dislocations. A broad range of face centered cubic metals (copper, nickel, silver, rhodium, and platinum) and nanovoid sizes and spacings are treated, altogether spanning void size–to–dislocation stacking fault width ratios from less than unity to ten. Material γ-surfaces, calculated from ab initio methods, are input directly into the formulation. The analysis reveals that the critical bypass stress scales linearly with the linear void fraction, effective isotropic shear modulus, and ratio of the intrinsic to unstable stacking fault energies. With only a few exceptions, the critical stress is controlled by the stress required for the leading partial to impinge the voids (to move within range of the attractive image stress field of the void). When the void diameter is nearly an order of magnitude greater than the stacking fault width, the mechanism determining critical strength shifts to the stress for the dislocation to breakaway after partially cutting the void. Furthermore, this situation corresponds to that treated by line tension models and is realized here for Pt, with a sub-nanometer stacking fault width.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Approximation of refrigerant thermophysical properties using neural networks to speed up transient thermofluid simulations

Accurate and efficient evaluations of refrigerant thermophysical properties and their partial derivatives are essential for transient simulations of thermofluid systems, where several computations need to be executed at each integration time step. Since the utilization of an Equation of State for retrieving properties based on a pair of independent inputs typically involves numerical iterations in solution procedures, when the input variables differ from the refrigerant state variables employed in dynamic models, a variety of approaches including lookup table interpolation and curve fitting have been developed to explicitly approximate these properties based on the state variables, and consequently eliminate internal iterations. This paper presents an alternative method that exploits derivative-informed neural networks to model refrigerant properties explicitly from inputs of pressure and enthalpy, while ensuring consistent partial derivatives generated by differentiating the neural networks. Computational speed and accuracy of the proposed approach are demonstrated via transient simulations of a discretized heat exchanger model in Modelica, and comparisons against other property evaluation routines. Simulation results indicate that the proposed approach can realize a significant speedup with negligible discrepancies in predicted transients. The method is implemented in an open-source Modelica library.

Ma, Jiacheng↗
DOE OSTI2020

Oxidation of phenolic compounds during autothermal pyrolysis of lignocellulose

Fast pyrolysis is traditionally defined as the rapid decomposition of organic material in the absence of oxygen to produce primarily a liquid product known as bio-oil. However, the introduction of small amounts of oxygen to the process holds prospects of internally generating the energy needed for pyrolysis. The present study investigates the partial oxidation of lignin-derived compounds during pyrolysis, which generates both carbon oxides and aromatic carbonyl compounds. Analysis of lignin derived phenolic compounds was performed to determine if the composition had changed under oxidative conditions. NMR analyses indicates aromatic carbonyls increased under oxidative conditions, with a corresponding decrease in phenolic hydroxyl groups. Finally, model phenolic compounds were pyrolyzed to help understand the role of partial oxidation during autothermal pyrolysis of lignocellulosic biomass.

09 BIOMASS FUELS↗
DOE OSTI2021

Understanding the microstructural stability in a y’-strengthened Ni-Fe-Cr-Al-Ti alloy

Ni-Fe-Cr-Al-Ti alloys, with Ni levels near 50 wt.%, have the potential to develop a microstructure consisting of a face-centered cubic ? matrix with the homogeneous precipitation of fine ordered ?’ precipitates similar to traditional Ni-based superalloys with significantly greater Ni content. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), atom probe tomography (APT), and CALPHAD -based thermodynamic modeling were employed to understand the phase stabilities and microstructural evolution in an age-hardenable Ni-27Fe-18Cr-1Co-1.6Al-3.75Ti-1.2Mo-0.03C (wt%) alloy. The primary heat-treatment of solution annealing at 1121°C for 4h and age-hardening treatment at 760 °C for 16h resulted in a microstructure consisting of fine ?’ precipitates in an austenitic matrix along with grain boundary carbides, consistent with thermodynamic calculations. Long-term aging at 900 °C for 250h resulted in the coarsening of ?’ along with a change in the morphology of the precipitates from spherical to a more cuboidal shape. In addition, ? phase formation was observed concomitant with the partial dissolution of the ?’ phase. The ability of computational thermodynamic models to predict microstructural characteristics is discussed.

Gwalani, Bharat↗
DOE OSTI2024

Molecular basis for dual functions in pilus assembly modulated by the lid of a pilus-specific sortase

The biphasic assembly of Gram-positive pili begins with the covalent polymerization of distinct pilins catalyzed by a pilus-specific sortase, followed by the cell wall anchoring of the resulting polymers mediated by the housekeeping sortase. In Actinomyces oris, the pilus-specific sortase SrtC2 not only polymerizes FimA pilins to assemble type 2 fimbriae with CafA at the tip, but it can also act as the anchoring sortase, linking both FimA polymers and SrtC1-catalyzed FimP polymers (type 1 fimbriae) to peptidoglycan when the housekeeping sortase SrtA is inactive. To date, the structure-function determinants governing the unique substrate specificity and dual enzymatic activity of SrtC2 have not been illuminated. Here, we present the crystal structure of SrtC2 solved to 2.10-Å resolution. SrtC2 harbors a canonical sortase fold and a lid typical for class C sortases and additional features specific to SrtC2. Structural, biochemical, and mutational analyses of SrtC2 reveal that the extended lid of SrtC2 modulates its dual activity. Specifically, we demonstrate that the polymerizing activity of SrtC2 is still maintained by alanine-substitution, partial deletion, and replacement of the SrtC2 lid with the SrtC1 lid. Strikingly, pilus incorporation of CafA is significantly reduced by these mutations, leading to compromised polymicrobial interactions mediated by CafA. In a srtA mutant, the partial deletion of the SrtC2 lid reduces surface anchoring of FimP polymers, and the lid-swapping mutation enhances this process, while both mutations diminish surface anchoring of FimA pili. Evidently, the extended lid of SrtC2 enables the enzyme the cell wall-anchoring activity in a substrate-selective fashion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization

Objective: The growing availability of electronic health records (EHR) data opens opportunities for integrative analysis of multi-institutional EHR to produce generalizable knowledge. A key barrier to such integrative analyses is the lack of semantic interoperability across different institutions due to coding differences. We propose a Multiview Incomplete Knowledge Graph Integration (MIKGI) algorithm to integrate information from multiple sources with partially overlapping EHR concept codes to enable translations between healthcare systems. Methods: The MIKGI algorithm combines knowledge graph information from (i) embeddings trained from the co-occurrence patterns of medical codes within each EHR system and (ii) semantic embeddings of the textual strings of all medical codes obtained from the Self-Aligning Pretrained BERT (SAPBERT) algorithm. Due to the heterogeneity in the coding across healthcare systems, each EHR source provides partial coverage of the available codes. MIKGI synthesizes the incomplete knowledge graphs derived from these multi-source embeddings by minimizing a spherical loss function that combines the pairwise directional similarities of embeddings computed from all available sources. MIKGI outputs harmonized semantic embedding vectors for all EHR codes, which improves the quality of the embeddings and enables direct assessment of both similarity and relatedness between any pair of codes from multiple healthcare systems. Results: With EHR co-occurrence data from Veteran Affairs (VA) healthcare and Mass General Brigham (MGB), MIKGI algorithm produces high quality embeddings for a variety of downstream tasks including detecting known similar or related entity pairs and mapping VA local codes to the relevant EHR codes used at MGB. Based on the cosine similarity of the MIKGI trained embeddings, the AUC was 0.918 for detecting similar entity pairs and 0.809 for detecting related pairs. For cross-institutional medical code mapping, the top 1 and top 5 accuracy were 91.0% and 97.5% when mapping medication codes at VA to RxNorm medication codes at MGB; 59.1% and 75.8% when mapping VA local laboratory codes to LOINC hierarchy. When trained with 500 labels, the lab code mapping attained top 1 and 5 accuracy at 77.7% and 87.9%. MIKGI also attained best performance in selecting VA local lab codes for desired laboratory tests and COVID-19 related features for COVID EHR studies. Compared to existing methods, MIKGI attained the most robust performance with accuracy the highest or near the highest across all tasks. Conclusions: The proposed MIKGI algorithm can effectively integrate incomplete summary data from biomedical text and EHR data to generate harmonized embeddings for EHR codes for knowledge graph modeling and cross-institutional translation of EHR codes.

Zhou, Doudou↗
DOE OSTI2024

Hydrogen activation by rhodium under the cover of a copper oxide thin film

Here, the activation of reactants by catalytically active metal sites at metal-oxide interfaces is important for understanding the effect of metal-support interactions on nanoparticle catalysts and for tuning activity and selectivity. Using a combined experimental and theoretical approach, we studied the activation of H 2 and the effect of CO poisoning on isolated Rh atoms completely or partially covered by a copper oxide (Cu 2 O) thin film. Temperature-programmed desorption (TPD) experiments conducted in ultra-high vacuum (UHV) show that neither a partially nor a fully oxidized Cu 2 O layer grown on a Rh/Cu(111) single-atom alloy can activate hydrogen in UHV. However, in situ ambient pressure X-ray photoelectron spectroscopy (AP-XPS) experiments performed at elevated H 2 pressures reveal that Rh significantly accelerates the reduction of these Cu 2 O thin films by hydrogen. Remarkably, the fastest reduction rate is observed for the fully oxidized sample with all Rh sites covered by Cu 2 O. Both TPD and AP-XPS data demonstrate that these covered Rh sites are inaccessible to CO, indicating that Rh under Cu 2 O is active for H 2 dissociation but cannot be poisoned by CO. In contrast, an incomplete oxide film leaves some of the Rh sites exposed and accessible to CO, and hence prone to CO poisoning. Density functional theory calculations demonstrate that unlike many reactions in which hydrogen activation is rate limiting, the rate-determining step in the dissociation of H 2 on thin-film Cu 2 O with Rh underneath is the adsorption of H 2 on the buried Rh site, and once adsorbed, the dissociation of H 2 is barrierless. These calculations also explain why H 2 can only be activated at higher pressures. Together, these results highlight how different the reactivity of atomically dispersed Rh in Cu can be depending on its accessibility through the oxide layer, providing a way to engineer Rh sites that are active for hydrogen activation but resilient to CO poisoning.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Transported PDF Modeling of Compressible Turbulent Reactive Flows by using the Eulerian Monte Carlo Fields Method

Although the transported probability density function (PDF) method has been developed for decades, its application has been mainly focused on the low-Mach number flow problems. This work extends the transported PDF method to compressible flow problems. The Eulerian Monte Carlo fields (EMCF) solution method is employed to solve the transported PDF equation for compressible flow problems. A pseudo stagnation enthalpy is introduced and its stochastic partial differential equation is derived to ensure total energy conservation numerically. A new mixing model called interaction by partial exchange with mean (IPEM) is introduced to expand the available choices of mixing models for the EMCF method. The consistency of the EMCF method is examined for solving the transported PDF equation. Numerical implementation details are discussed, such as the density coupling between the compressible flow solver and the EMCF solver, discretization schemes for the mixing terms and the stochastic terms. The implemented compressible flow solver coupled with the EMCF solver is verified and validated in a series of test cases with increasing level of complexity, ranging from a statistically one-dimensional turbulent mixing layer to a self-excited resonance model rocket combustor. It is observed that in general with the increase of compressibility, there is an increase in the sensitivity of the modeling results to the different models and algorithms. This makes it necessary to develop a thorough understanding of the model sensitivity in order to develop a robust and accurate simulation solver for highly compressible turbulent reactive flows. The thermo-acoustic instability inside the model rocket combustor case is captured reasonably, which demonstrates the overall capability of the developed compressible turbulent combustion solver based on the transported PDF method.

42 ENGINEERING↗
DOE OSTI2021

B-PINNs: Bayesian Physics-informal Neural Networks for Forward and Inverse PDE Problems with Noisy Data

We propose a Bayesian physics-informed neural network (B-PINN) to solve both forward and inverse nonlinear problems described by partial differential equations (PDEs) and noisy data. In this Bayesian framework, the Bayesian neural network (BNN) combined with a PINN for PDEs serves as the prior while the Hamiltonian Monte Carlo (HMC) or the variational inference (VI) could serve as an estimator of the posterior. B-PINNs make use of both physical laws and scattered noisy measurements to provide predictions and quantify the aleatoric uncertainty arising from the noisy data in the Bayesian framework. Compared with PINNs, in addition to uncertainty quantification, B-PINNs obtain more accurate predictions in scenarios with large noise due to their capability of avoiding overfitting. We conduct a systematic comparison between the two different approaches for the B-PINNs posterior estimation (i.e., HMC or VI), along with dropout used for quantifying uncertainty in deep neural networks. Our experiments show that HMC is more suitable than VI with mean field Gaussian approximation for the B-PINNs posterior estimation, while dropout employed in PINNs can hardly provide accurate predictions with reasonable uncertainty. Finally, we replace the BNN in the prior with a truncated Karhunen-Loève (KL) expansion combined with HMC or a deep normalizing flow (DNF) model as posterior estimators. The KL is as accurate as BNN and much faster but this framework cannot be easily extended to high-dimensional problems unlike the BNN based framework.

Non linear PDEs, Noisy data, Bysian physics inform↗
DOE OSTI2021

Tusas: A fully implicit parallel approach for coupled phase-field equations

In this study, we develop a fully-coupled, fully-implicit approach for phase-field modeling of solidification in metals and alloys. Predictive simulation of solidification in pure metals and metal alloys remains a significant challenge in the field of materials science, as microstructure formation during the solidification process plays a critical role in the properties and performance of the solid material. Our simulation approach consists of a finite element spatial discretization of the fully-coupled nonlinear system of partial differential equations at the microscale, which is treated implicitly in time with a preconditioned Jacobian-free Newton-Krylov method. The approach is algorithmically scalable as well as efficient due to an effective preconditioning strategy based on algebraic multigrid and block factorization. We implement this approach in the open-source Tusas framework, which is a general, flexible tool developed in C++ for solving coupled systems of nonlinear partial differential equations. The performance of our approach is analyzed in terms of algorithmic scalability and efficiency, while the computational performance of Tusas is presented in terms of parallel scalability and efficiency on emerging heterogeneous architectures. We demonstrate that modern algorithms, discretizations, and computational science, and heterogeneous hardware provide a robust route for predictive phase-field simulation of microstructure evolution during additive manufacturing.

97 MATHEMATICS AND COMPUTING↗