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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Evidence for galaxy assembly bias in BOSS CMASS redshift-space galaxy correlation function

ABSTRACT Building accurate and flexible galaxy–halo connection models is crucial in modelling galaxy clustering on non-linear scales. Recent studies have found that halo concentration by itself cannot capture the full galaxy assembly bias effect and that the local environment of the halo can be an excellent indicator of galaxy assembly bias. In this paper, we propose an extended halo occupation distribution (HOD) model that includes both a concentration-based assembly bias term and an environment-based assembly bias term. We use this model to achieve a good fit (χ2/degrees of freedom = 1.35) on the 2D redshift-space two-point correlation function (2PCF) of the Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxy sample. We find that the inclusion of both assembly bias terms is strongly favoured by the data and the standard five-parameter HOD model is strongly rejected. More interestingly, the redshift-space 2PCF drives the assembly bias parameters in a way that preferentially assigns galaxies to lower mass haloes. This results in galaxy–galaxy lensing predictions that are within 1σ agreement with the observation, alleviating the perceived tension between galaxy clustering and lensing. We also showcase a consistent 3σ–5σ preference for a positive environment-based assembly bias that persists over variations in the fit. We speculate that the environmental dependence might be driven by underlying processes such as mergers and feedback, but might also be indicative of a larger halo boundaries such as the splashback radius. Regardless, this work highlights the importance of building flexible galaxy–halo connection models and demonstrates the extra constraining power of the redshift-space 2PCF.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Main and Satellite Features in the Ni 2p XPS of NiO

The origin and assignment of the complex main and satellite XPS features of the cations in ionic compounds has been the subject of extensive theoretical studies using different methods. There is agreement that within a molecular orbital model one needs to take into account different types of configurations. Specifically, those where a core electron is removed but no other configuration changes are made and those where in addition to ionization there are also shake or charge transfer changes to the ionic configuration. However, there are strong disagreements about the assignment of XPS features to these configurations. The present work is directed toward resolving the origin of main and satellite features for the Ni 2p XPS of NiO based on ab initio molecular orbital wavefunctions for a cluster model of NiO. A major problem in earlier ab initio XPS studies of ionic compounds has been the use of a common set of orbitals that was not able to properly describe all the ionic configurations that contribute to the full XPS spectra. This is resolved in the present work by using orbitals that are optimized for averages of the occupations of the different configurations that contribute to the XPS. The approach of using State Averaged orbitals is validated through comparisons between different averages and through use of higher order excitations in the wavefunctions for the ionic states. It represents a major extension of our earlier work on the main and satellite features of the Fe 2p XPS of Fe 2 O 3 and proves the reliability and the generality of the assignments of the character and origin of the different features of the XPS obtained with orbitals optimized for State Averages. These molecular orbital methods permit the characterization of the ionic states in terms of the importance of shake excitations and of the coupling of ionization of 2p 1/2 and 2p 3/2 spin-orbit split sub shells. Further, the work lays the foundation for definitive assignments of the character of main and satellite XPS features and points to their origin in the electronic structure of the material.

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

Data-Driven Prediction and Optimization of Energy Use for Transit Fleets of Electric and ICE Vehicles

Due to the high upfront cost of electric vehicles, many public transit agencies can afford only mixed fleets of internal combustion and electric vehicles. Optimizing the operation of such mixed fleets is challenging because it requires accurate trip-level predictions of electricity and fuel use as well as efficient algorithms for assigning vehicles to transit routes. We present a novel framework for the data-driven prediction of trip-level energy use for mixed-vehicle transit fleets and for the optimization of vehicle assignments, which we evaluate using data collected from the bus fleet of CARTA, the public transit agency of Chattanooga, TN. We first introduce a data collection, storage, and processing framework for system-level and high-frequency vehicle-level transit data, including domain-specific data cleansing methods. We train and evaluate machine learning models for energy prediction, demonstrating that deep neural networks attain the highest accuracy. Based on these predictions, we formulate the problem of minimizing energy use through assigning vehicles to fixed-route transit trips. We propose an optimal integer program as well as efficient heuristic and meta-heuristic algorithms, demonstrating the scalability and performance of these algorithms numerically using the transit network of CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Spatially explicit terrestrial carbon densities for calibrating the carbon cycle in human-Earth system Models

Soil and vegetation carbon stocks play a critical role in human-Earth system models. These stocks (denominated as densities in MgC/ha) affect variables such as land use change emissions and also influence land use change pathways under climate forcing scenarios where terrestrial carbon is assigned a carbon price. Here we present reharmonized soil and vegetation carbon densities both at the 5-arcmin resolution grid cell level and also aggregated to 235 water sheds for 4 land use types (Cropland, Grazed land, Urban land and unmanaged vegetation) and 15 unmanaged land cover types. Moreover, we use the distribution of carbon within and across pixels to define statistical "states" of carbon, once again differentiated by land type. These statistical states are used to define a range of possible carbon values that can be used for defining initial conditions of soil and vegetation carbon in human-Earth system models. We implement these data in a state-of-the-art multi sector dynamics model, namely the Global Change Analysis Model (GCAM), and show that these new data improve several land use responses, especially when terrestrial carbon is assigned a carbon price.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mechanism of astatine and bismuth sorption on extraction chromatography resins from nitric acid media

Systematic study of astatine (At) sorption on extraction chromatography resins from nitric acid media has been performed at Texas A&M University. This work covers commercially available resins such as LN, TK400, SR, TRU, and UTEVA. Acquiring an understanding of At behavior in up to 4 M HNO 3 solutions is a key step to develop a rapid and reliable system for At separation and purification. The determined distribution coefficients are greater than 20 for all the resins studied, reaching 400 for TRU and UTEVA resins. The sorption uptake decreases in the order: TRU ≳ UTEVA >TK400 ≳ SR >LN. For each resin a thermodynamic model has been developed to suggest a possible mechanism of At sorption and corresponding sorption constants have been estimated. Literature data along with new results on bismuth (Bi) sorption by studied resins in nitric acid media have been reviewed and a mathematical model to describe its behavior has been suggested. A ratio of corresponding fit functions of At and Bi assigned to the same resin and acidity has been used to estimate separation factors of these elements. Furthermore, only the TRU resin is not suitable for efficient At isolation from Bi, while the other four resins demonstrate promising results.

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

High-Pressure Rate Rules for Ether Alkylperoxy Radical Isomerization

The first isomerization reaction of an alkylperoxy (RO 2 ) radical holds significant importance in low-temperature oxidation, as it governs the branching ratios of the hydroperoxyalkyl (QOOH) radicals, which influence the competition between the chain-propagation and chain-branching reactions. In this study, we systematically calculated high-pressure rate rules for the RO 2 isomerization reaction of monoethers, exploring 5-, 6-, 7-, and 8-membered ring transition states. Primary, secondary, and tertiary carbon sites, where both the abstracting peroxy group and the abstracted hydrogen are located, were considered, with particular emphasis on distinguishing between secondary carbons adjacent (alpha) and nonadjacent to the ether functional group. Using the G4//B3LYP/6-311++G(2df,2pd) level of theory and the transition state theory, we estimated the rate constants and the Arrhenius coefficient for over 120 possible isomerization reactions. We examined the effect of ring size and ring atoms, revealing that 6- and 7-membered ring isomerizations were generally the fastest. The impact of the ether functional group on transition states was investigated by comparing reactions with identical ring size, peroxy, and radical positions, but with the ether functional group positioned either outside (i.e., out) or inside (i.e., in) the transition state ring, leading to differences in the rate constants. When comparing to analogous alkane rate constants, differences of up to an order of magnitude were observed, underscoring the need for caution when assigning rate rules by analogy. We applied our rate constants in the di-iso-butyl ether kinetic model and evaluated their influence on low-temperature chemistry finding that they altered the branching ratios by up to a factor of 9, highlighting the significance of site-specific rate constants for more accurate low-temperature modeling.

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

Life history strategies among soil bacteria—dichotomy for few, continuum for many

Abstract Study of life history strategies may help predict the performance of microorganisms in nature by organizing the complexity of microbial communities into groups of organisms with similar strategies. Here, we tested the extent that one common application of life history theory, the copiotroph-oligotroph framework, could predict the relative population growth rate of bacterial taxa in soils from four different ecosystems. We measured the change of in situ relative growth rate to added glucose and ammonium using both 18O–H2O and 13C quantitative stable isotope probing to test whether bacterial taxa sorted into copiotrophic and oligotrophic groups. We saw considerable overlap in nutrient responses across most bacteria regardless of phyla, with many taxa growing slowly and few taxa that grew quickly. To define plausible life history boundaries based on in situ relative growth rates, we applied Gaussian mixture models to organisms’ joint 18O–13C signatures and found that across experimental replicates, few taxa could consistently be assigned as copiotrophs, despite their potential for fast growth. When life history classifications were assigned based on average relative growth rate at varying taxonomic levels, finer resolutions (e.g., genus level) were significantly more effective in capturing changes in nutrient response than broad taxonomic resolution (e.g., phylum level). Our results demonstrate the difficulty in generalizing bacterial life history strategies to broad lineages, and even to single organisms across a range of soils and experimental conditions. We conclude that there is a continued need for the direct measurement of microbial communities in soil to advance ecologically realistic frameworks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The O K -2 V spectrum of CO: the influence of the second core-hole

Using synchrotron radiation in the tender X-ray regime, a photoelectron spectrum showing the formation of single site double-core-hole pre-edge states, involving the K shell of the O atom in CO, has been recorded by means of high-resolution electron spectroscopy. The experimentally observed structures have been simulated, interpreted and assigned, employing state-of-the-art ab initio quantum chemical calculations, on the basis of a theoretical model, accounting for their so-called direct or conjugate character. Features appearing above the double ionization threshold have been reproduced by taking into account the strong mixing between multi-excited and continuum states. The shift of the σ* resonance below the double ionization threshold, in combination with the non-negligible contributions of multi-excited configurations in the final states reached, gives rise to a series of avoided crossings between the different potential energy curves.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Clusters have edges: the projected phase-space structure of SDSS redMaPPer clusters

ABSTRACT We study the distribution of line-of-sight velocities of galaxies in the vicinity of Sloan Digital Sky Survey (SDSS) red-sequence Matched-filter Probabilistic Percolation (redMaPPer) galaxy clusters. Based on their velocities, galaxies can be split into two categories: galaxies that are dynamically associated with the cluster, and random line-of-sight projections. Both the fraction of galaxies associated with the galaxy clusters, and the velocity dispersion of the same, exhibit a sharp feature as a function of radius. The feature occurs at a radial scale Redge ≈ 2.2Rλ, where Rλ is the cluster radius assigned by redMaPPer. We refer to Redge as the ‘edge radius’. These results are naturally explained by a model that further splits the galaxies dynamically associated with a galaxy cluster into a component of galaxies orbiting the halo and an infalling galaxy component. The edge radius Redge constitutes a true ‘cluster edge’, in the sense that no orbiting structures exist past this radius. A companion paper tests whether the ‘halo edge’ hypothesis holds when investigating the full three-dimensional phase-space distribution of dark matter substructures in numerical simulations, and demonstrates that this radius coincides with a suitably defined splashback radius.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

RAVEN Theory Manual

RAVEN is a software framework able to perform parametric and stochastic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the thermohydraulic code RELAP-7, currently under development at Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose stochastic and uncertainty quantification platform, capable of communicating with any system code. In fact, the provided Application Programming Interfaces (APIs) allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating system response and explore input space using various sampling schemes such as Monte Carlo, grid, or Latin hypercube. However, RAVEN strength lies in its system feature discovery capabilities such as: constructing limit surfaces, separating regions of the input space leading to system failure, and using dynamic supervised learning techniques. The development of RAVEN started in 2012 when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework arose. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concepts developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just to identify the frequency of an event potentially leading to a system failure, but the proximity (or lack thereof) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. peak pressure in a pipe) is exceeded under certain conditions. Most of the capabilities, implemented having RELAP-7 as a principal focus, are easily deployable to other system codes. For this reason, several side activates have been employed (e.g. RELAP5-3D, any MOOSE-based App, etc.) or are currently ongoing for coupling RAVEN with several different software. The aim of this document is to provide a set of commented examples that can help the user to become familiar with the RAVEN code usage.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Techno-Economic Assessment for Opportunities to Integrate Algae Farming with Wastewater Treatment

This report investigates the economic and scalability potential for algal biomass production based on opportunities to couple algae farming with wastewater treatment (WWT). This activity was motivated in part by a recent influx of technology developers who are currently in various stages of planning, construction, and operation of algae facilities for treating municipal wastewater, all making claims of tremendous economic potential for algal WWT relative to other more traditional WWT methods when viewing treated wastewater as the primary product output and algal biomass as a secondary coproduct. In addition to solving for minimum biomass selling price (MBSP) for a farm configured to maximize biomass production while minimizing water footprint (when sourcing makeup water from local groundwater resources at added cost), the algal WWT cases evaluated here also solved for MBSP while assigning a treatment credit as a means to valorize the treated water as a coproduct in the farm model. This enables a consistent comparison against the National Renewable Energy Laboratory’s standard algae farm models.

09 BIOMASS FUELS↗
DOE OSTI2026

Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events

Danovo Energy Solution's presented its paper named: Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events at the 2026 Georgia Tech Fault & Disturbance Analysis Conference. The full paper can be found at OSTI ID# 3169150 Paper Abstract—Phasor Measurement Units (PMUs) stream time synchronized, high-resolution measurements from the grid, enabling data-driven techniques for event detection and classification. Accurate event classification improves grid reliability and stability. Events can be detected by varying numbers of PMUs and exhibit different durations depending on the event type. This variability challenges standard classifiers that require uniform input sizes. Moreover, multiple events may coincide, which increases classification complexity. Standard classifiers assign each instance to the class with the highest predicted probability, whereas overlapping events may exhibit comparable probabilities across multiple classes. In this study, to handle data size variability, we extract a wide range of time–frequency domain features from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, LightGBM, Support Vector Machine, and Multilayer Perceptron. To account for overlapping events, a probabilistic post-processing step is applied. For a given data instance, if multiple predicted class probabilities exceed 30% and the differences between them are less than 10%, the event is assigned to multiple classes. Experiments using real-world PMU data demonstrate that the Random Forest and XGBoost models achieve the highest accuracy, while the proposed post-processing method yields perfect classification performance on external unseen test sets.

Nematirad, Reza [Danova Energy Solutions]↗
DOE OSTI2021

Rotation Curves of Galaxies and Their Dependence on Morphology and Stellar Mass

Here, we study how stellar rotation curves (RCs) of galaxies are correlated on average with morphology and stellar mass (M star ) using the final release of Sloan Digital Sky Survey IV MaNGA data. We use the visually assigned T-types for the morphology indicator, and adopt a functional form for the RC that can model non-flat RCs at large radii. We discover that within the radial coverage of the MaNGA data, the popularly known flat rotation curve at large radii applies only to the particular classes of galaxies, i.e., massive late types (T-type ≥ 1, M star ≳ 10 10.8 M⊙) and S0 types (T-type = –1 or 0, M star ≳ 10 10.0 M⊙). The RC of late-type galaxies at large radii rises more steeply as M star decreases, and its slope increases to about +9 km s –1 kpc –1 at M star ≈ 10 9.7 M⊙. By contrast, elliptical galaxies (T-type ≤ –2) have descending RCs at large radii. Their slope becomes more negative as M star decreases, and reaches as negative as –15 km s –1 kpc –1 at M star ≈ 10 10.2 M⊙. We also find that the inner slope of the RC is highest for elliptical galaxies with M star ≈ 10 10.5 M⊙, and decreases as T-type increases or M star changes away from 10 10.5 M⊙. The velocity at the turnover radius R t is higher for higher M star , and R t is larger for higher M star and later T-types. We show that the inner slope of the RC is coupled with the central surface stellar mass density, which implies that the gravitational potential of central regions of galaxies is dominated by baryonic matter. With the aid of simple models for matter distribution, we discuss what determines the shapes of RCs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events

This paper is the basis for a presentation help at the 2026 Georgia Tech Fault & Disturbance Analysis Conference, which can be found at OSTI # 3168287 Paper Abstract—Phasor Measurement Units (PMUs) stream time synchronized, high-resolution measurements from the grid, enabling data-driven techniques for event detection and classification. Accurate event classification improves grid reliability and stability. Events can be detected by varying numbers of PMUs and exhibit different durations depending on the event type. This variability challenges standard classifiers that require uniform input sizes. Moreover, multiple events may coincide, which increases classification complexity. Standard classifiers assign each instance to the class with the highest predicted probability, whereas overlapping events may exhibit comparable probabilities across multiple classes. In this study, to handle data size variability, we extract a wide range of time–frequency domain features from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, LightGBM, Support Vector Machine, and Multilayer Perceptron. To account for overlapping events, a probabilistic post-processing step is applied. For a given data instance, if multiple predicted class probabilities exceed 30% and the differences between them are less than 10%, the event is assigned to multiple classes. Experiments using real-world PMU data demonstrate that the Random Forest and XGBoost models achieve the highest accuracy, while the proposed post-processing method yields perfect classification performance on external unseen test sets.

Nematirad, Reza [Danovo Energy Solutions]↗
DOE OSTI2025

Photometry of Outer Solar System Objects from the Dark Energy Survey. II. A Joint Analysis of Trans-Neptunian Absolute Magnitudes, Colors, Light Curves and Dynamics

For the 696 trans-Neptunian objects (TNOs) with absolute magnitudes 5.5 < H r < 8.2 detected in the Dark Energy Survey, we characterize the relationships between their dynamical state and physical properties—namely H r , indicating size; colors, indicating surface composition; and flux variation semiamplitude A, indicating asphericity and surface inhomogeneity. We seek “birth” physical distributions that can recreate these parameters in every dynamical class. We show that the observed colors of these TNOs are consistent with two Gaussian distributions in griz space, “near-infrared bright” (NIRB) and “near-infrared faint” (NIRF), presumably an inner and outer birth population, respectively. We find a model in which both the NIRB and NIRF H r and A distributions are independent of current dynamical states, supporting their assignment as birth populations. All objects are consistent with a common rolling p(H r ), but NIRF objects are significantly more variable. Cold classicals (CCs) are purely NIRF, while hot classical (HC), scattered, and detached TNOs are consistent with ≈ 70% NIRB and the resonance NIRB fractions show significant variation. The NIRB components of the HCs and of some resonances have broader inclination distributions than the NIRFs, i.e. their current dynamics retains information about birth location. We find evidence for radial stratification within the birth NIRB population, in that HC NIRBs are on average redder than detached or scattered NIRBs; a similar effect distinguishes CCs from other NIRFs. We estimate total object counts and masses of each class within our H r range. These results will strongly constrain models of the outer solar system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Resolving the Chemical Formula of Nesquehonite via NMR Crystallography, DFT Computation, and Complementary Neutron Diffraction

Nesquehonite is a magnesium carbonate mineral relevant to carbon sequestration envisioned for carbon capture and storage of CO 2 . Its chemical formula remains controversial today, assigned as either a hydrated magnesium carbonate [MgCO 3 · 3H 2 O], or a hydroxy- hydrated- magnesium bicarbonate [Mg(HCO 3 )OH · 2H 2 O]. Here, the resolution of this controversy is central to understanding this material‘s thermodynamic, phase, and chemical behavior. In an NMR crystallography study, using rotational-echo double-resonance 13 C{ 1 H} (REDOR), 13 C- 1 H distances are determined with precision, and the combination of 13 C static NMR lineshapes and density functional theory (DFT) calculations are used to model different H atomic coordinates. [MgCO 3 · 3H 2 O] is found to be accurate, and evidence from neutron powder diffraction bolsters these assignments. Refined H positions can help understand how H-bonding stabilizes this structure against dehydration to MgCO 3 . More broadly, these results illustrate the power of NMR crystallography as a technique for resolving questions where X-ray diffraction is inconclusive.

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

An energy-based study of the embedded element method for explicit dynamics

Abstract The embedded finite element technique provides a unique approach for modeling of fiber-reinforced composites. Meshing fibers as distinct bundles represented by truss elements embedded in a matrix material mesh allows for the assignment of more specific material properties for each component rather than homogenization of all of the properties. However, the implementations of the embedded element technique available in commercial software do not replace the material of the matrix elements with the material of the embedded elements. This causes a redundancy in the volume calculation of the overlapping meshes leading to artificially increased stiffness and mass. This paper investigates the consequences in the energy calculations of an explicit dynamic model due to this redundancy. A method for the correction of the edundancy within a finite element code is suggested which removes extra energy and is shown to be effective at correcting the energy calculations for large amounts of redundant volume.

Martin, Valerie A.↗