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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

High ALDH activity defines ovarian cancer stem-like cells with enhanced invasiveness and EMT progress which are responsible for tumor invasion

Highlights: • Pluripotent, invasive and EMT-related genes are positively correlated. • The definition of ovarian ALDH{sup high} CSCLs is verified by their higher colony-formation, multipotent-genes expression and tumorigenicity. • Ovarian ALDH{sup high} CSCLs display advanced invasiveness, EMT progress and apoptosis-resistance. • ALDH{sup high} CSCLs take chief charge of EOC invasion, due to their elevated stemness and metastatic features. Epithelial ovarian cancer (EOC) is highly metastatic and current therapeutics are unsatisfactory. Cancer stem/stem-like cells (CSCs/CSCLs) represent a rare population of undifferentiated oncogenic cells responsible for tumor initiation and maintenance. We identified ovarian cancer ALDH{sup high} (aldehyde dehydrogenase) population could perform not only strengthened CSCLs properties embodied in colony-formation, CSCs-markers expression, and tumorigenesis in vivo, but also a greater invasive capacity with advanced EMT progress and anti-apoptosis compared with ALDH{sup low} cells. Furthermore, both the stemness and aggressive features, along with ALDH{sup high} percentages were in positive association with the invasiveness of cell lines for sorting, indicating the promotive role of ALDH{sup high} CSCLs in EOC neoplasia and metastasis, since the whole tumor was derived from the CSCLs with hyperactive self-renewal and aggression. Collectively, this study illustrates the interplay between ALDH{sup high} CSCLs and EOC invasion, and offers a novel application target for the EOC oncotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Activation of TLR3 and its adaptor TICAM-1 increases miR-21 levels in extracellular vesicles released from human cells

Highlights: • Activation of TLR3 increases miR-21 levels in extracellular vesicles. • TLR3 requires TICAM-1 adaptor to increase miR-21 levels in extracellular vesicles. • YBX-1 is involved in TLR3-mediated increase of miR-21 levels. Pattern-recognition receptors (PRRs) recognizes viral RNAs and trigger the innate immune responses. Toll-like receptor 3 (TLR3), a PRR, recognizes viral double-stranded RNA (dsRNA) in endolysosomes, whereas cytoplasmic dsRNA is sensed by another PRR, MDA5. TLR3 and MDA5 utilize TICAM-1 and MAVS, respectively, to trigger the signal for inducing innate immune responses. Extracellular vesicles (EVs) include the exosomes and microvesicles; an accumulating body of evidence has shown that EVs delivers functional RNA, such as microRNAs (miRNAs), to other cells and thus mediate intercellular communications. Therefore, EVs carrying miRNAs affect innate immune responses in macrophages and dendritic cells. However, the mechanism underlying the regulation of miRNA levels in EVs remains unclear. To elucidate the mechanism, we sought to reveal the pathway that control miRNA expression levels in EVs. Here, we found that TLR3 stimulation increased miR-21 levels in EVs released from various types of human cells. Ectopic expression of the TLR3 adaptor, TICAM-1, increased miR-21 levels in EVs but not intracellular miR-21 levels, suggesting that TICAM-1 augmented sorting of miR-21 to EVs. In contrast, the MDA5 adaptor, MAVS, did not increase miR-21 levels in EVs. The siRNA for TICAM-1 reduced EV miR-21 levels after stimulation of TLR3. Collectively, our data indicate a novel role of the TLR3-TICAM-1 pathway in controlling miR-21 levels in EVs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Effect of long non-coding RNA H19 on oxidative stress and chemotherapy resistance of CD133+ cancer stem cells via the MAPK/ERK signaling pathway in hepatocellular carcinoma

Highlights: • The H19 expression is higher in HCC tissues than in adjacent normal tissues. • CD133-positive Huh7 cells account for (99.4 ± 3.6)% by flow cytometry. • Inhibition of H19 induces OS in CD133 + cancer stem cells. • Inhibition of H19 reverses chemoresistance in CD133 + cancer stem cells. • Inhibition of H19 contributes to inactivation of MAPK/ERK signaling pathway. We explored the ability of a long non-coding RNA H19, to influence oxidative stress (OS) and chemotherapy resistance of CD133 + cancer stem cells via the MAPK/ERK signaling pathway in HCC. HCC tissues with corresponding adjacent normal tissues were collected. CD133 + HuH7 cells were sorted and assigned into five groups. Quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were performed to determine expression levels mRNAs and proteins. Levels of reactive oxygen species (ROS) and malonaldehyde (MDA), and activity of superoxide dismutase (SOD) were measured. Cell viability was analyzed by MTT assay and cell apoptosis by flow cytometry. Compared with adjacent normal tissues, the H19 expression level was higher and MAPK and ERK protein levels were lower in HCC tissues. Compared with the blank group, in the pcDNA-H19 group, H19 expression level, MAPK and ERK protein levels, MDR1 and GST-π expression levels were increased, ROS and MDA levels were decreased, SOD activity was weakened, cell viability was promoted, and cell apoptosis was inhibited; in the siH19 group, H19 expression level, MAPK and ERK protein levels, MDR1 and GST-π expression levels were reduced, ROS and MDA levels were elevated, SOD activity was enhanced, cell viability was inhibited, and cell apoptosis was promoted. There was no significant difference among blank, NC and pcDNA-H19 + PD98059 groups. The study provides evidence that downregulation of H19 may induce OS and reverse chemotherapy resistance of CD133 + cancer stem cells by blocking the MAPK/ERK signaling pathway in HCC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Mouse model of chorea-acanthocytosis exhibits male infertility caused by impaired sperm motility as a result of ultrastructural morphological abnormalities in the mitochondrial sheath in the sperm midpiece

Chorea-acanthocytosis (ChAc) is an autosomal recessive hereditary disease characterized by neurodegeneration in the striatum and acanthocytosis caused by loss-of-function mutations in the Vacuolar Protein Sorting 13 Homolog A (VPS13A) gene, which encodes chorein. We previously produced a ChAc-model mouse with a homozygous deletion of exons 60–61 in Vps13a, which corresponded to the human disease mutation. We found that male ChAc-model mice exhibited complete infertility as a result of severely diminished sperm motility. Immunocytochemical study revealed that chorein-like immunoreactivity is abundant only in the midpiece, mitochondria-rich region, of the sperm of wild type mice. They showed no significant differences from wild types in terms of the adenosine 5′-triphosphate (ATP) concentration of their sperm, sperm count, or sexual activity. Electron microscopy revealed abnormal ultrastructural morphology of the mitochondria in the midpiece of sperm from ChAc-model mice. These results suggest that chorein is essential in mouse sperm for the maintenance of ultrastructural mitochondrial morphology and sperm motility.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Effects of Icaritin on the physiological activities of esophageal cancer stem cells

Highlights: • CSCs were used instead of using cancer cells. • The effect of Icaritin on the Hedgehog and Wnt signaling pathway was investigated. • Our study found that Icaritin down-regulated the level of Hedgehog, Smo and Gli in Hedgehog pathway, up-regulated GSK3β and down-regulated Wnt and β-catenin in Wnt pathway, indicating that Icaritin may inhibit the activity of esophageal CSCs through regulating the expression of proteins in important pathways related to esophageal cancer. Icaritin is a compound extracted from herb, recent study have found it is able to influence the activity of various types of cancer. Our aim was to investigate the effects of Icaritin on the physiological activities of esophageal cancer stem cells (CSCs). In this study, esophageal cancer cells were cultured and CD133 positive esophageal CSCs were sorted by flow cytometry. Changes in the physiological activity of esophageal CSCs following treatment with different concentrations of Icaritin (0, 12.5, 25, 50, and 100 μmol/L) were evaluated. The CCK-8 method and Transwell assay were used to determine the effects of Icaritin on the proliferation, migration, and invasion of esophageal CSCs. Flow cytometery was used to investigate its effect on the apoptosis of CSCs. The effect of Icaritin on the expression of proteins in Wnt and Hedgehog signaling pathways were determined using western blot test. Consequently, Icaritin inhibited the proliferation, migration, and invasion of esophageal CSCs in a dose-dependent manner. It promoted cell apoptosis, and influenced the levels of proteins in Wnt and Hedgehog signaling pathways. It may act as a promising drug in the therapy of esophageal cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Identification of human immunodeficiency virus type-1 Gag-TSG101 interaction inhibitors by high-throughput screening

Highlights: • Development of HTS system based on ELISA targeting Gag-TSG101 interaction. • Screening of 9600 compounds identified 11 compounds inhibiting Gag-TSG101 binding. • Hit compounds, HSM-9 and HSM-10 potently reduced HIV-1 replication. The interaction between viral protein Gag and cellular protein tumor susceptibility gene 101 (TSG101) is a crucial step in the HIV-1 replication cycle. This interaction initiates the viral assembly/budding via the cellular endosomal sorting complexes required for transport (ESCRT) pathway, making it a potential target for antiviral therapy. Here we developed a simple, robust, and reliable high-throughput screening (HTS) system based on enzyme-linked immunosorbent assay (ELISA) to identify compounds that inhibit HIV-1 replication by targeting Gag-TSG101 interaction. Through screening of the 9600-compound library using the established HTS system, several hit compounds, which inhibited Gag-TSG101 interaction, were identified. Subsequent assays revealed two hit compounds, HSM-9 and HSM-10, which have antiviral activity against CD4{sup +} T cell-tropic NL4-3 and macrophage-tropic JR-CSF HIV-1 strains. These results suggest that our established HTS system is an indispensable tool for the identification of HIV-1 Gag-TSG101 interaction inhibitors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Improving biomass and lipid yields of Desmodesmus armatus and Chlorella vulgaris through mutagenesis and high-throughput screening

Advancement of microalgae for use as biofuel feedstock depends on bioprospecting novel strains and then applying classical strain improvement techniques to enhance desirable traits. Here we successfully demonstrate this approach using two novel strains of green algae, identified as Desmodesmus armatus and Chlorella vulgaris, to improve biomass and lipid yields. UV irradiation was utilized to generate random mutations and the resulting populations were analyzed via flow cytometry to quantify lipid fluorescence while enriching for high lipid variants using fluorescence activated cell sorting. Secondary screening was performed via in situ fluorescence staining to identify the single highest lipid producing mutants from each strain. This approach produced a Desmodesmus armatus mutant that exhibited both increased biomass productivity and higher lipid content, which doubled lipid yield from the culture. The resulting Chlorella vulgaris mutant exhibited an increase in growth only, resulting in a 33% increase in lipid yield.

09 BIOMASS FUELS↗
DOE OSTI2021

The crystal and coordination chemistry of neptunium in all its oxidation states: An expanded structural hierarchy of neptunium compounds

We report structures of 388 neptunium-bearing crystal structures are sorted into an expanded structural hierarchy and examined. The majority of structures contain Np(V) (149), Np(VI) (99), or Np(IV) (91) whereas structures containing Np(II), Np(III), Np(VII), or more than one oxidation state are rare. Coordination geometry of Np(V) and Np(VI) compounds is dominated by the approximately linear neptunyl cation. Actinyl–actinyl interactions (AAIs) are most prevalent in Np(V) compounds and are observed in 48% of these extended structures. Prismatic coordination geometries are commonly observed in Np(IV) compounds. Np(III) organometallic complexes display a variety of coordination modes. Coordination chemistry of Np(VII) compounds is dominated by the tetra-oxido core. Updated average bond length values are provided for Np(IV), Np(V), Np(VI), and Np(VII) compounds and updated bond valence parameters for Np(IV) are reported. A graphical notation system for neptunyl structures coordinated by organic ligands was developed to facilitate discussion and identify similarities between neptunyl compounds coordinated by oxyanions and neptunyl compounds coordinated by organic ligands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Vaccine-Induced Antibodies that Neutralize Group 1 and Group 2 Influenza A Viruses

Antibodies capable of neutralizing divergent influenza A viruses could form the basis of a universal vaccine. Here, from subjects enrolled in an H5N1 DNA/MIV-prime-boost influenza vaccine trial, we sorted hemagglutinin cross-reactive memory B cells and identified three antibody classes, each capable of neutralizing diverse subtypes of group 1 and group 2 influenza A viruses. Co-crystal structures with hemagglutinin revealed that each class utilized characteristic germline genes and convergent sequence motifs to recognize overlapping epitopes in the hemagglutinin stem. All six analyzed subjects had sequences from at least one multidonor class, and—in half the subjects—multidonor-class sequences were recovered from >40% of cross-reactive B cells. By contrast, these multidonor-class sequences were rare in published antibody datasets. Vaccination with a divergent hemagglutinin can thus increase the frequency of B cells encoding broad influenza A-neutralizing antibodies. We propose the sequence signature-quantified prevalence of these B cells as a metric to guide universal influenza A immunization strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Asymmetric and non-stoichiometric glycoprotein recognition by two distinct antibodies results in broad protection against ebolaviruses

Several ebolaviruses cause outbreaks of severe disease. Vaccines and monoclonal antibody cocktails are available to treat Ebola virus (EBOV) infections, but not Sudan virus (SUDV) or other ebolaviruses. Current cocktails contain antibodies that cross-react with the secreted soluble glycoprotein (sGP) that absorbs virus-neutralizing antibodies. By sorting memory B cells from EBOV infection survivors, we isolated two broadly reactive anti-GP monoclonal antibodies, 1C3 and 1C11, that potently neutralize, protect rodents from disease, and lack sGP cross-reactivity. Both antibodies recognize quaternary epitopes in trimeric ebolavirus GP. 1C11 bridges adjacent protomers via the fusion loop. 1C3 has a tripartite epitope in the center of the trimer apex. One 1C3 antigen-binding fragment anchors simultaneously to the three receptor-binding sites in the GP trimer, and separate 1C3 paratope regions interact differently with identical residues on the three protomers. A cocktail of both antibodies completely protected nonhuman primates from EBOV and SUDV infections, indicating their potential clinical value.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Development of a VRC01-class germline targeting immunogen derived from anti-idiotypic antibodies

An effective HIV-1 vaccine will likely need to elicit broadly neutralizing antibodies (bNAbs). Broad and potent VRC01-class bNAbs have been isolated from multiple infected individuals, suggesting that they could be reproducibly elicited by vaccination. Several HIV-1 envelope-derived germline-targeting immunogens have been designed to engage naive VRC01-class precursor B cells. However, they also present off-target epitopes that could hinder development of VRC01-class bNAbs. We characterize a panel of anti-idiotypic monoclonal antibodies (ai-mAbs) raised against inferred-germline (iGL) VRC01-class antibodies. By leveraging binding, structural, and B cell sorting data, we engineered a bispecific molecule derived from two aimAbs; one specific for VRC01-class heavy chains and one specific for VRC01-class light chains. The bispecific molecule preferentially activates iGL-VRC01 B cells in vitro and induces specific antibody responses in a murine adoptive transfer model with a diverse polyclonal B cell repertoire. This molecule represents an alternative non-envelope-derived germline-targeting immunogen that can selectively activate VRC01-class precursors in vivo.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching

Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.

Metamaterial↗
DOE OSTI2026

Computational methods in solution-based plastics purification

Plastic waste can be recycled into resins with near-virgin properties by solution-based purification processes that selectively dissolve polymers, remove contaminants, or detach printing residues. Here, in this review, we examine computational methods for predicting the behavior governing solution-based plastic purification, motivated by the vast polymer–solvent–contaminant compositional space. We discuss thermodynamic and machine learning methods for predicting polymer–solvent and polymer–contaminant interaction and review physics-based molecular dynamics simulations that resolve molecular-scale phenomena within polymer matrices inaccessible to screening methods. We highlight how these methods have informed experimental design for dissolution-based recycling and solvent-based contaminant removal. Finally, we discuss the prospective role of agentic AI in integrating these computational tools with real-time sorting data to adapt purification conditions to the compositional variability of real post-consumer feedstocks. This review charts a path toward computationally guided solution-based purification workflows that can respond to the complexity inherent in plastic waste streams.

Altamimi, Ali [Univ. of Wisconsin, Madison, WI (Un↗
DOE OSTI2017

The role of correlations in uncertainty quantification of transportation relevant fuel models

Large reaction mechanisms are often used to describe the combustion behavior of transportation-relevant fuels like gasoline, where these are typically represented by surrogate blends, e.g., n-heptane/iso-octane/toluene. We describe efforts to quantify the uncertainty in the predictions of such mechanisms at realistic engine conditions, seeking to better understand the robustness of the model as well as the important reaction pathways and their impacts on combustion behavior. In this work, we examine the importance of taking into account correlations among reactions that utilize the same rate rules and those with multiple product channels on forward propagation of uncertainty by Monte Carlo simulations. Automated means are developed to generate the uncertainty factor assignment for a detailed chemical kinetic mechanism, by first uniquely identifying each reacting species, then sorting each of the reactions based on the rate rule utilized. Simulation results reveal that in the low temperature combustion regime for iso-octane, the majority of the uncertainty in the model predictions can be attributed to low temperature reactions of the fuel sub-mechanism. The foundational, or small-molecule chemistry (C 0 -C 4 ) only contributes significantly to uncertainties in the predictions at the highest temperatures (Tc=900 K). Accounting for correlations between important reactions is shown to produce non-negligible differences in the estimates of uncertainty. Including correlations among reactions that use the same rate rules increases uncertainty in the model predictions, while accounting for correlations among reactions with multiple branches decreases uncertainty in some cases. Significant non-linear response is observed in the model predictions depending on how the probability distributions of the uncertain rate constants are defined.Finally, we concluded that care must be exercised in defining these probability distributions in order to reduce bias, and physically unrealistic estimates in the forward propagation of uncertainty for a range of UQ activities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Accounting for uncertainty in RCCE species selection

A framework is presented to quantify, based on Bayesian evidence, the relative plausibility of species se- lection options in rate-controlled constrained equilibrium (RCCE) reduced chemical models, accounting for uncertainty in the kinetic parameters and experimental data used to refine them. This approach bal- ances the joint goals of matching available data and avoiding overfitting, which is well-understood to limit extrapolative capacity for true prediction. The methodology is applied to homogeneous autoigni- tion, where predictions are known to be particularly sensitive to chemical model details, specially at low temperatures. It is first introduced for hydrogen–air autoignition using an established mechanism, then demonstrated in two applications of methane–air autoignition using the larger GRI-1.2 mechanism. This larger mechanism significantly increases the computational cost of model selection (though not of the subsequent application in predictions), which is alleviated with a time-scale-guided pre-sorting strategy. Uses and extensions of this new formulation are discussed.

08 HYDROGEN↗
DOE OSTI2020

Effects of cluster expansion on the locations of phase transition boundary as a first step to quantify uncertainty in first principles statistical mechanics framework

Predicting phase diagrams from first principle calculations eliminates the need of tedious experimental trials and errors. Fully automating first principle phase diagram calculations without any sort of human intervention has been a long daunting task and troubling scientific communities for decades. This grand problem remains not fully resolved, largely due to the vastly high-dimensional parameter space associated with density functional theory, cluster expansion, lattice Monte Carlo, and the substantial uncertainty propagating through a set of complex simulations. As a first step to tackle this grand problem, we reported a first demonstration of how sensitive phase boundary locations can be to various cluster expansion fittings and input DFT training data. To the best knowledge of the authors, this study reported the first ever attempt to quantify uncertainty in first principles statistical mechanics framework. In addition, a semi-automated phase transition detection algorithm has been devised in this paper to deal with the associated statistical errors and uncertainties from Monte Carlo method and its predecessor DFT calculations and cluster expansions. This algorithm has been applied in a classical cluster expansion Mg-Cd binary alloy system to detect phase transitions at various locations of phase diagram using different cluster expansions to demonstrate its predictive power and quantify uncertainties. The results suggested that using Chebyshev basis function shifted the transition locations toward the dilute solid solution phase and expanded the phase stability of concentrated ordered phases to wider composition range. The addition of perturbed defect configurations into training data set lowered the order-disorder transition temperature to be away from true transition temperature, suggesting the transition nature is indeed configurational disorder dominated rather than defect assisted. Finally, we found that the weighting has negligible effect on the transition locations, except for the case of using Chebyshev basis function to fit all non-weighted configurations that can be susceptible to Monte Carlo sampling hysteresis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

ClassNMSW- a real-time classification approach for non-recycled municipal solid waste using hyperspectral imaging

Real-time classification of non-recycled municipal solid waste (NMSW) is essential for efficient valorization. This study introduces ClassNMSW, a comprehensive framework for classifying 22 NMSW subclasses under industrial constraints by using hyperspectral imaging (HSI). A primary innovation of this work is the development of a variance-controlled spectral extraction algorithm. Unlike traditional methods that rely on simple averaging, this approach systematically investigates the extent of pixel extraction to minimize the loss of critical chemical information while maximizing data reduction thus ensuring high spectral fidelity with low computational cost. The approach developed in this work integrates automated, computer-vision-based background removal, eliminating the need for the manual thresholding common in current literature. To resolve ambiguities among chemically similar subclasses, a tiered classification and multi-camera fusion strategy (NIR17 and NIR22) is implemented. Results demonstrate that ClassNMSW achieves an object-wise weighted accuracy of 98.70% for single-sensor configurations and 100% under sensor fusion. A novel rolling-window strategy satisfies desired end-to-end latency of <2 s, satisfying the strict deterministic requirements of high-speed industrial sorting environments. The ClassNMSW framework provides a scalable foundation for advancing circularity and resource recovery in large-scale waste valorization operations.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

An Eulerian multimaterial framework for simulating high-explosive aquarium tests

Aquarium tests of cylindrical high-explosive charges provide optical data of the detonation front velocity and shape, propagation of the shock wave in the surrounding water, and expansion rates of the detonation products behind the front. Data from aquarium experiments is often used for calibration of reactive burn models based on phenomenological equations of state (EOS) and reaction rate laws. This paper presents a multimaterial numerical modeling framework to solve the 2D axisymmetric reactive Euler equations for high-explosive aquarium tests, in particular for ammonium nitrate - fuel oil (ANFO) explosives. An extension of the Ghost Fluid Method (GFM) is used to handle the dynamic material interfaces for the ANFO explosion products, the charge-confining material (polymethyl methacrylate PMMA), and the surrounding water. This study analyzes the sensitivity of calculations (both computational efficiency and numerical accuracy) to different algorithms for the material interface models including the original GFM versus Riemann solver-based strategies. A novel method for defining the left and right states in the interfacial Riemann problem eliminates the need for sorting or nodal interpolation during the projection along the material interface. Numerical tests indicate that populating the interface node values using the Riemann solution mitigate the overheating error observed in steady-state calculations. Solution convergence and computational efficiency are explored as a function of the spatial and temporal order of the schemes. Results from the computational model with analytical equations of state and fitted reaction rate parameters show very good quantitative agreement with experimentally observed detonation front velocity, reaction products expansion, and shock wave propagation in the surrounding water for a cylindrical ANFO charge encased in PMMA. Finally, the proposed modeling framework, in conjunction with experimental tests, provides a reliable tool to assess equations of state and reaction rate expressions for reactive burn models of confined high explosives.

42 ENGINEERING↗