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At least 1,531 records · Page 85

Prospective Phase 2 Study of Radiation Therapy Dose and Volume De-escalation for Elective Neck Treatment of Oropharyngeal and Laryngeal Cancer

The required elective nodal dose and volumes for head and neck intensity modulated radiation therapy have largely been extrapolated from conventional radiation therapy fields. In this prospective, dual-center, phase 2 study, we investigated the efficacy and tolerability of reduced elective nodal volume and dose in oropharyngeal and laryngeal squamous cell carcinoma.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Investigation of the mechanical and microstructural evolution of a Cu based bulk metallic glass during ion irradiation

Ion irradiation and annealing experiments were performed on Cu 60 Zr 20 Hf 10 Ti 10 bulk metallic glass (BMG) specimens to investigate their irradiation- and temperature-induced microstructural and mechanical property evolution. For the ion irradiations, samples were exposed to 9 MeV Ni 3+ ions to a midrange (~1.2 μm depth) dose of 10 displacements per atom (dpa) at temperatures ranging from room temperature to 360 °C (the corresponding peak dose at ~2.8 μm depth was ~25 dpa). Bulk X-ray diffraction (XRD) and transmission electron microscopy (TEM) characterization revealed that the alloy did not crystallize during irradiation up to 290 °C but did partially crystallize at 360 °C. XRD analysis revealed that the crystallization which occurred in the sample irradiated at 360 °C was caused by thermal effects instead of irradiation displacement damage. Subsequent Rietveld refinement analysis of the XRD measurements revealed the presence of two distinct crystal phases, namely a CuTiZr hexagonal structure belonging to the P63/mmc space group and a CuTi tetragonal structure belonging to the P4/mmm space group. Nanoindentation experiments revealed that no pronounced hardness changes occurred in the specimens irradiated at room temperature and 290°C, although significant hardening was observed in the sample irradiated at 360 °C. The significant increase in the hardness at 360°C was ascribed to thermally induced partial crystallization of the alloy instead of the ion irradiation. In general, the results of the nanoindentation experiments and XRD characterization suggest that although the Cu BMG exhibits good stability during irradiation at temperatures up to 290 °C it is not suitable for irradiation environments where the temperature is 360 °C for extended periods of time. The Lam and Chong extrapolation method, which has been used to study the indentation size effect (ISE) in amorphous alloys, was employed to quantify how irradiation and temperature affect this type of behavior in the BMG. However, the poor linear fitting of the indentation hardness data by this model indicate that a new ISE model is likely needed to quantify indentation hardening in BMGs.

36 MATERIALS SCIENCE↗

Translating nanoparticle dosimetry from conventional in vitro systems to occupational inhalation exposures

As encouraged by Toxicity Testing in the 21st Century, researchers increasingly apply high-throughput in vitro approaches to identify and characterize nanoparticle hazards, including conventional aqueous cell culture systems to assess respiratory hazards. Translating nanoparticle dose from conventional toxicity testing systems to relevant human exposures remains a major challenge for assessing occupational risk of nanoparticle exposures. Here, we explored existing computational tools and data available to translate nanoparticle dose metrics from cellular test systems to inhalation exposures of silver nanoparticles in humans. We used the Multiple-Path Particle Dosimetry (MPPD) Model to predict deposition of humans exposed to 20 and 110 nm silver nanoparticles at 0.9 µg/m3 over an 8 hr period, the proposed a National Institute of Occupational Safety and Health (NIOSH) recommended exposure limit (REL). MPPD predicts 1.88 and 0.98 µg of silver deposited in an 8 hr period for 20 and 110 nm nanoparticles, respectively, with 20 nm particles displaying nearly 11-fold higher total surface area deposited. Peak nanoparticle concentrations occurred more proximal in the pulmonary tract compared to mass deposition patterns (generation 5 vs. generations 20-21, respectively) due to regional differences in lung lining fluid volumes. Assuming 0.4% nanoparticle dissolution by mass as previously measured, we predict peak concentrations of silver ions in cells of 0.24 and 0.17 µg/mL for 20 and 110 nm particles, respectively. Both predicted concentrations are below the measured toxic threshold of 1.7 µg/mL of silver ions in cells from in vitro assessments. Assuming 4% dissolution by mass, we predict 10-fold higher silver concentrations in tissues, peaking at 2.4 and 1.7 µg/mL, for 20 and 110 nm nanoparticles respectively, exceeding the observed in vitro toxic threshold and highlighting the importance and sensitivity of dissolution rates. Overall, this approach offers a framework for extrapolating nanotoxicity results from in vitro cell culture systems to human exposures. Aligning appropriate dose metrics from in vitro and in vivo hazard characterizations and human pulmonary doses from occupational exposures are critical components for successful nanoparticle risk assessment and worker protection and provide guidance for designing future in vitro studies aimed at relevant human exposures.

Smith, Jordan N.↗

Thermodynamic and kinetic analysis of the melt spinning process of Fe-6.5 wt.% Si alloy

Here, the microstructural evolution of Fe-6.5 wt.% Si alloy during rapid solidification was studied over a quenching rate of 4 × 10 4 K/s to 8 ×10 5 K/s. The solidification and solid-state diffusional transformation processes during rapid cooling were analyzed via thermodynamic and kinetic calculations. The Allen-Cahn theory was adapted to model the experimentally measured bcc_B2 antiphase domain sizes under different cooling rates. The model was calibrated based on the experimentally determined bcc_B2 antiphase domain sizes for different wheel speeds and the resulting cooling rates. Good correspondence of the theoretical and experimental data was obtained over the entire experimental range of cooling rates. Along with the asymptotic domain size value at the infinite cooling rates, the developed model represents a reliable extrapolation for the cooling rate > 10 6 K/s and allows one to optimize the quenching process.

36 MATERIALS SCIENCE↗

Structures of two novel crystal forms of Aspergillus oryzae alpha amylase (taka-amylase)

The structures of Aspergillus oryzae α-amylase were determined in a tetragonal crystal, having one molecule as asymmetric unit, and a monoclinic crystal with two molecules as asymmetric unit. Both crystal forms were obtained from trace contaminants of an old commercial lipase preparation. Structures were determined and refined to 1.65 Å and 1.43 Å resolution respectively. The latter crystal has a non-crystallographic (NCS) twofold axis within the asymmetric unit. Glycosylation at Asn197 is evident, and in the tetragonal crystal can be seen to include three, partially disordered sugar residues following the initial N-acetyl glucosamine (NAG). Superposition of the tetragonal crystal model on the α-amylases from Bacillus subtilis (PDB:1BAG), pig pancreas (PDB:3L2L), and barley (PDB:1AMY), show a high degree of coincidence, particularly for the (β/α)8-barrel domains, and especially within the active site. Using this structural agreement between amylases, we extrapolated the binding model of a six residue, limit dextrin found in pig pancreas α-amylase to the A. oryzae enzyme model, which predicts substrate interacting amino acid residues.

59 BASIC BIOLOGICAL SCIENCES↗

Probing the Self-Assembly dynamics of cellulose nanocrystals by X-ray photon correlation spectroscopy

Charge-stabilized colloidal cellulose nanocrystals (CNCs) can self-assemble into higher-ordered chiral nematic structures by varying the volume fraction. The assembly process exhibits distinct dynamics during the isotropic to liquid crystal phase transition, which can be elucidated using X-ray photon correlation spectroscopy (XPCS). Anionic CNCs were dispersed in propylene glycol (PG) and water spanning a range of volume fractions, encompassing several phase transitions. Coupled with traditional characterization techniques, XPCS was conducted to monitor the dynamic evolution of the different phases. Additionally, simulated XPCS results were obtained using colloidal rods and compared with the experimental data, offering additional insights into the dynamic behavior of the system. The results indicate that the particle dynamics of CNCs undergo a stepped decay in three stages during the self-assembly process in PG, coinciding with the observed phases. The phase transitions are associated with a total drop of Brownian diffusion rates by four orders of magnitude, a decrease of more than a thousand times slower than expected in an ideal system of repulsive Brownian rods. Given the similarity in the phase behaviors in CNCs dispersed in PG and in water, we hypothesize that these dynamic behaviors can be extrapolated to other polar solvent environments. Importantly, these findings represent the direct measurement of CNC dynamics using XPCS, underscoring the feasibility of directly assessing the dynamic behavior of other rod-like colloidal suspensions.

36 MATERIALS SCIENCE↗

Establishing a geochemical heterogeneity model for a contaminated vadose zone – Aquifer system

A large set of sediment samples from a 1600 m2 experimental plot within a 2.2 km2 vadose zone and groundwater uranium (VI) plume were subject to physical, chemical, and mineralogic characterization. The plot is being used for field experimentation on U(VI) recharge and transport processes within a persistent groundwater plume that exists in the groundwater-river interaction zone of the Columbia River at the U.S. DOE Hanford site. The samples were obtained during the installation of 35 tightly spaced (10 m separation) groundwater monitoring wells. The characterization measurements for each sample included total contaminant concentrations (U and Cu primarily), bicarbonate extractable U(VI), sequential 238U(VI) contaminant desorption Kd, 233U(VI) adsorption Kd, grain size distribution, surface area, extractable poorly crystalline Fe(III) oxides, and mineralogy. The characterization objective was to inform a conceptual model of coupled processes controlling the anomalous longevity of the plume, and to quantify the spatial heterogeneity of the contaminant inventory and the primary properties effecting reactive transport. Correlations were drawn between chemical, physical, and reaction properties, and Gaussian simulation was used to compute multiple 3-D realizations of extractable U(VI), the 233U(VI) adsorption Kd, and the distribution of the reactive < 2 mm fraction. Adsorbed contaminant U(VI) was highest in the vadose zone and the zone of seasonal water table fluctuation lying at its base. Adsorbed U(VI) was measureable, but low, in the groundwater plume region where very high hydraulic conductivities existed. The distribution of adsorbed U(VI) displayed no apparent correlation with sediment physical or chemical properties. Desorption [238U(IV)] and adsorption [233U(VI)] Kd values showed appreciable differences due to mass transfer controlled surface complexation and the effects of long subsurface residence times. The 233U(VI) adsorption Kd, a combined measure of surface complexation strength and site concentration, was relatively uniform throughout the domain, displaying correlation with fines distribution and surface area. The characterization results revealed U(VI) supplied to the groundwater plume through spatially heterogeneous recharge from residual contamination in the zone of seasonal water table fluctuation, and transport of U(VI) controlled by weak, kinetically-controlled surface complexation in the coarse-textured saturated zone. Geostatistical relationships for the adsorbed contaminant U distribution in the characterization domain allow an extrapolation to inventory at the plume scale, a critical unknown for remedial action.

contaminant heterogeniety, uranium groundwater plu↗

Uncertainty analysis of multi-rate kinetics of uranium desorption from sediments

A multi-rate expression for uranyl [U(VI)] surface complexation reactions has been proposed to describe diffusion-limited U(VI) sorption/desorption in heterogeneous subsurface sediments. An important assumption in the rate expression is that its rate constants follow a certain type probability distribution. In this paper, a Bayes-based, Differential Evolution Markov Chain method was used to assess the distribution assumption and to analyze parameter and model structure uncertainties. U(VI) desorption from a contaminated sediment at the US Hanford 300 Area, Washington was used as an example for detail analysis. The results indicated that: 1) the rate constants in the multi-rate expression contain uneven uncertainties with slower rate constants having relative larger uncertainties; 2) the lognormal distribution is an effective assumption for the rate constants in the multi-rate model to simualte U(VI) desorption; 3) however, long-term prediction and its uncertainty may be significantly biased by the lognormal assumption for the smaller rate constants; and 4) both parameter and model structure uncertainties can affect the extrapolation of the multi-rate model with a larger uncertainty from the model structure. The results provide important insights into the factors contributing to the uncertainties of the multi-rate expression commonly used to describe the diffusion or mixing-limited sorption/desorption of both organic and inorganic contaminants in subsurface sediments.

Environmental Molecular Sciences Laboratory↗

Robust verification of stochastic simulation codes

We introduce a robust verification tool for computational codes, which we call Stochastic Robust Extrapolation based Error Quantification (StREEQ). Unlike the prevalent Grid Convergence Index (GCI) [1] method, our approach is suitable for both stochastic and deterministic computational codes and is generalizable to any number of discretization variables. Building on ideas introduced in the Robust Verification [2] approach, we estimate the converged solution and orders of convergence with uncertainty using multiple fits of a discretization error model. In contrast to Robust Verification, we perform these fits to many bootstrap samples yielding a larger set of predictions with smoother statistics. Here, bootstrap resampling is performed on the lack-of-fit errors for deterministic code responses, and directly on the noisy data set for stochastic responses. This approach lends a degree of robustness to the overall results, capable of yielding precise verification results for sufficiently resolved data sets, and appropriately expanding the uncertainty when the data set does not support a precise result. For stochastic responses, a credibility assessment is also performed to give the analyst an indication of the trustworthiness of the results. Furthermore, this approach is suitable for both code and solution verification, and is particularly useful for solution verification of high-consequence simulations..

97 MATHEMATICS AND COMPUTING↗

Learning functional priors and posteriors from data and physics

In this work, we develop a new Bayesian framework based on deep neural networks to be able to extrapolate in space-time using historical data and to quantify uncertainties arising from both noisy and gappy data in physical problems. Specifically, the proposed approach has two stages: (1) prior learning and (2) posterior estimation. At the first stage, we employ the physics-informed Generative Adversarial Networks (PI-GAN) to learn a functional prior either from a prescribed function distribution, e.g., Gaussian process, or from historical data and physics. At the second stage, we employ the Hamiltonian Monte Carlo (HMC) method to estimate the posterior in the latent space of PI-GANs. In addition, we use two different approaches to encode the physics: (1) automatic differentiation, used in the physicsinformed neural networks (PINNs) for scenarios with explicitly known partial differential equations (PDEs), and (2) operator regression using the deep operator network (DeepONet) for PDE-agnostic scenarios. We then test the proposed method for (1) meta-learning for one-dimensional regression, and forward/inverse PDE problems (combined with PINNs); (2) PDE-agnostic physical problems (combined with DeepONet), e.g., fractional diffusion as well as saturated stochastic (100-dimensional) flows in heterogeneous porous media; and (3) spatial-temporal regression problems, i.e., inference of a marine riser displacement field using experimental data from the Norwegian Deepwater Programme (NDP). The results demonstrate that the proposed approach can provide accurate predictions as well as uncertainty quantification given very limited scattered and noisy data, since historical data could be available to provide informative priors. In summary, the proposed method is capable of learning flexible functional priors, e.g., both Gaussian and non-Gaussian process, and can be readily extended to big data problems by enabling mini-batch training using stochastic HMC or normalizing flows since the latent space is generally characterized as low dimensional.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An immersed interface method for the 2D vorticity-velocity Navier-Stokes equations with multiple bodies

We present an immersed interface method for the vorticity-velocity form of the 2D Navier Stokes equations that directly addresses challenges posed by nonconvex immersed bodies, multiply connected domains, and the calculation of force distributions on immersed surfaces. The immersed interface method is re-interpreted as a polynomial extrapolation of flow quantities and boundary conditions into the immersed solid bodies, reducing computational cost and enabling simulations with nonconvex bodies that could not be discretized with previous immersed interface methods. In the flow, the vorticity transport equation is discretized using a conservative finite difference scheme and explicit Runge-Kutta time integration. The velocity reconstruction problem is transformed to a scalar Poisson equation that is discretized with conservative finite differences, and solved using an FFT-accelerated iterative algorithm. The use of conservative differencing throughout leads to exact enforcement of a discrete Kelvin's theorem, allowing for simulations with multiply connected domains and outflow boundaries that have challenged other immersed interface vortex methods. We also explore novel methods for recovering time-dependent pressure distributions on immersed bodies within a vorticity-based method and present a novel control volume formulation for recovering aerodynamic moments from only the vorticity and velocity fields. The method achieves second order spatial accuracy and third order temporal accuracy, and is validated on a variety of 2D flows in internal and free-space domains.

97 MATHEMATICS AND COMPUTING↗

Effective Half-Life of Caesium-137 in Various Environmental Media at the Savannah River Site

During the operational history of the Savannah River Site (SRS), many different radionuclides have been released from site facilities into the SRS environment. However, only a relatively small number of pathways, most importantly 137 Cs in fish and deer, have contributed significantly to doses and risks to the public. The “effective” half-lives (T e ) of 137 Cs (which include both physical decay and environmental dispersion) in Savannah River floodplain soil and vegetation and in fish and white-tailed deer from the SRS were estimated using long-term monitoring data. For 1974–2011, the T e s of 137 Cs in Savannah River floodplain soil and vegetation were 17.0 years (95% CI = 14.2–19.9) and 13.4 years (95% CI = 10.8–16.0), respectively. These T e s were greater than in a previous study that used data collected only through 2005 as a likely result of changes in the flood regime of the Savannah River. Field analyses of 137 Cs concentrations in deer collected during yearly controlled hunts at the SRS indicated an overall T e of 15.9 years (95% CI = 12.3–19.6) for 1965–2011; however, the T e for 1990–2011 was significantly shorter (11.8 years, 95% CI = 4.8–18.8) due to an increase in the rate of 137 Cs removal. The shortest T e s were for fish in SRS streams and the Savannah River (3.5–9.0 years), where dilution and dispersal resulted in rapid 137 Cs removal. Long-term data show that T e s are significantly shorter than the physical half-life of 137 Cs in the SRS environment but that they can change over time. Therefore, it is desirable have a long period of record for calculating Tes and risky to extrapolate T e s beyond this period unless the processes governing 137 Cs removal are clearly understood.

54 ENVIRONMENTAL SCIENCES↗

Fate and transport of uranium (VI) in weathered saprolite

We conducted batch and column experiments to investigate sorption and transport of uranium (U) in the presence of saprolite derived from interbedded shale, limestone, and sandstone sequences. Sorption kinetics were measured at two initial concentrations (C0; 1, 10 mM) and three soil:solution ratios (Rs/w; 0.005, 0.25, 2 kg/L) at pH 4.5 (pH of the saprolite). The rate of U loss from solution (mmole/L/h) increased with increasing Rs/w. Uranium sorption exhibited a fast phase with 80% sorption in the first eight hours for all C0 and Rs/w values and a slow phase during which the reaction slowly approached (pseudo) equilibrium over the next seven days. The pH-dependency of U sorption was apparent in pH sorption edges. U(VI) sorption increased over the pH range 4e6, then decreased sharply at pH > 7.5. U(VI) sorption edges were well described by a surface complexation model using calibrated parameters and the reaction network proposed by Waite et al. (1994). Sorption isotherms measured using the same Rs/w and pH values showed a solids concentration effect where U(VI) sorption capacity and affinity decreased with increasing solids concentration. Moreover, this effect may have been due to either particle aggregation or competition between U(VI) and exchangeable cations for sorption sites. The surface complexation model with calibrated parameters was able to predict the general sorption behavior relatively well, but failed to reproduce solid concentration effects, implying the importance of appropriate design if batch experiments are to be utilized for dynamic systems. Transport of U(VI) through the packed column was significantly retarded. We also conducted transport simulations using the reactive transport model HydroGeoChem (HGC) v5.0 that incorporated the surface complexation reaction network used to model the batch data. Model parameters reported by Waite et al. (1994) provided a better prediction of U transport than optimized parameters derived from our sorption edges. The results presented in this study highlight the challenges in defining appropriate conditions for batch-type experiments used to extrapolate parameters for transport models, and also underline a gap in our ability to transfer batch results to transport simulations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Core-scale numerical simulation and comparison of breakdown of shale and resulting fractures using sc-CO 2 and water as injectants

Supercritical carbon dioxide (sc-CO 2 ) is an alternative to water for stimulation of low permeability systems such as shale gas and geothermal resources. Previously core-scale experimental studies have compared the behavior of CO 2 to water injection for sample breakdown. Due to differences in experimental setup and core sample preparation, inconsistent or even apparently contradictory conclusions have resulted. To reconcile this contradiction, a phase-field numerical model is applied to understand hydraulic fracturing experiments using Green River shale found in the literature. The finite element numerical model incorporates a rate-dependent phase-field fracture model developed separately to describe fracture initiation and growth. We investigate the impact of various material and fluid properties on the resulting fractures. Most importantly, we study the effect of fluid properties and boundary conditions on the breakdown pressure, including the direction of the resulting fracture plane. Model results predict that (1) sc-CO 2 injection in the laboratory may result in greater breakdown pressure than that of water under no-flow boundary conditions because lower viscosity sc-CO 2 may result in pressure build up at the core boundary that opposes fracture initiation and (2) lower viscosity sc-CO 2 also produces fast-propagating fractures that are less influenced by the bedding plane on their resulting fracture topology. Here our model offers a straightforward explanation and reconciliation of existing experimental observations, as well as a means to extrapolate to new conditions. Exploration of field-scale conditions suggests less pronounced or no elevation in breakdown pressure when sc-CO 2 is injected because the pressure build up effect at the system boundary is significantly less or absent at field length scales.

42 ENGINEERING↗

New perspectives on supercritical methane adsorption in shales and associated thermodynamics

Understanding methane adsorption behavior in shales is fundamental for optimizing shale gas development as the adsorbed methane is a large portion of the subsurface shale gas resource. However, the adsorption mechanism of supercritical methane in shales and associated thermodynamics are poorly understood because the equation of state of the adsorbed methane is unmeasurable. This work analyzed adsorption equilibria (up to 32 MPa and 393.15 K) using a rigorous framework that can account for non-ideal gas properties and accurately extrapolate absolute adsorption uptakes from measured adsorption isotherms. The framework also allows a straightforward calculation of thermodynamic potentials relevant to adsorption such as enthalpy and entropy. Modelling results show that methane adsorption isotherms in shale under different pressures and temperatures are represented by a two dimensional adsorption isotherm surface. The density of the adsorbed methane in shales depends on temperature and pressure, which is always lower than the liquid methane density but higher than the corresponding gaseous methane density. The temperature-dependent and pressure-dependent characteristics of adsorbed methane density leads to the corresponding temperature-dependent and pressure-dependent measured/absolute adsorption isotherms. The maximum adsorption uptake of shales is independent of temperature and pressure. The isosteric enthalpy/entropy of adsorption and enthalpy/entropy of adsorbed methane are found to be temperature- and surface coverage-dependent. These new findings not only clarify some historical misunderstandings of methane adsorption in shales for engineering application, but also provide a novel framework for interpreting methane adsorption behavior in shales and for determining the associated thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of the starting temperature of calorimetric measurements on the accuracy of determined magnetocaloric effect

Availability of a restricted heat capacity data range has a clear influence on the accuracy of calculated magnetocaloric effect, as confirmed by both numerical simulations and experimental measurements. Simulations using the Bean-Rodbell model show that, in general, the approximated magnetocaloric effect curves calculated using a linear extrapolation of the data starting from a selected temperature point down to zero kelvin deviate in a non-monotonic way from those correctly calculated by fully integrating the data from near zero temperatures. However, we discovered that a particular temperature range exists where the approximated magnetocaloric calculation provides the same result as the fully integrated one. These specific truncated intervals exist for both first and second order phase transitions and are the same for the adiabatic temperature change and magnetic entropy change curves. Here, the effect of this truncated integration in real samples was confirmed using heat capacity data of Gd metal and Gd 5 Si 2 Ge 2 compound measured from near zero temperatures.

36 MATERIALS SCIENCE↗

Scale bridging damage model for quasi-brittle metals informed with crack evolution statistics

Computationally efficient methods for bridging length scales, from highly resolved micro/meso-scale models that can explicitly model crack growth, to macro-scale continuum models that are more suitable for modeling large parts, have been of interest to researchers for decades. In this work, an improved brittle damage model is presented for the simulation of dynamic fracture in continuum scale quasi-brittle metal components. Crack evolution statistics, including the number, length, and orientation of individual cracks, are extracted from high-fidelity, finite discrete element method (FDEM) simulations and used to generate effective material moduli that reflect the material’s damaged state over time. This strategy allows for the retention of small-scale physical behaviors such as crack growth and coalescence in continuum scale hydrodynamic simulations. However, the high-fidelity simulations required to generate the crack statistics are computationally expensive. Thus, steps were taken to produce a flexible constitutive model to reduce the number of costly high-fidelity simulations needed to produce accurate results. A new stress based degradation criterion is introduced for the degradation of individual material zones. This allows for the development of a heterogeneous damage distribution within the bulk material. Then a flow stress model is added to the hydrodynamic simulation to account for plasticity in quasi-brittle materials. As a result, the effective moduli model can be applied to a larger range of materials. The effective moduli constitutive model is used to simulate beryllium flyer plate experiments. The results from the continuum scale simulations using statistics from a single high-fidelity simulation are found to be in excellent agreement with numerical and experimental velocity interferometer data. The same set of crack statistics are used to extrapolate the results of a higher rate flyer plate case using the effective moduli model. In conclusion, the extension of this model to higher rate cases shows promise for further reducing the number of costly high-fidelity simulations needed to generate crack statistics.

36 MATERIALS SCIENCE↗