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DOE OSTI2023

Application of Interparticle Spacing Model to Maximize Filler Content in Cementitious Pastes

One of the most impactful ways to reduce embodied carbon of concrete in the near term is by partially replacing Portland cement with supplementary cementitious materials and/or fillers. This article describes an approach to reduce cement content in concrete through the development of high filler, low water (HFLW) cementitious pastes. Pastes with cement content as low as 50% (% weight of fines) were designed by applying models that maximize the packing density of the granular system and that consider the characteristics of the materials to calculate interparticle spacing (IPS), thereby allowing to obtain pastes with higher solids concentration and lower water demand. Strong correlations were found between IPS, the consistency index of the Herschel-Bulkley rheological model, and cement hydration kinetic parameters of binary and ternary pastes containing a Portland limestone cement and up to two different types of ground limestone. The approach showed to be feasible for the design of HFLW concrete paste fraction.

Antunes da Silva, Denise↗

DOE OSTI2019

Infusible acrylic thermoplastic resins: Tailoring of chemorheological properties

Infusible liquid resins that polymerize into a thermoplastic are desirable for many applications. Similar to unsaturated and vinylester thermosetting systems, they consist of polymers dissolved in reactive monomer. This work presents a method to decrease cycle time by tuning the molecular weight and concentration of the predissolved polymer in the resin. Variation of these properties allows precise control of the viscosity which in turn controls the time at which peak exotherm is reached, the maximum temperature for a given part thickness, and cure time. In this work, predictive models for the viscosity dependence on molecular weight, polymer concentration, shear rate, and temperature are developed. Two fiberglass panels are fabricated and tested; one with a lower molecular weight ($M_w$~30 kg mol –1 ) poly(methyl methacrylate) dissolved in methyl methacrylate and the second with higher molecular weight ($M_w$~500 kg mol –1 ) predissolved polymer in the resin. Mechanical properties are indistinguishable but the lower molecular weight panel cures up to three times faster.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Multi-regime mixing modeling for local extinction and re-ignition in turbulent non-premixed flame by using LES/FDF method

Local extinction and re-ignition occur in turbulent non-premixed combustion when the Damköhler number is not large enough and the combustion is not fully mixing controlled. The occurrence of local extinction introduces locally extinguished flame holes followed by a premixed flame propagation toward the hole center to potentially reignite the flame. The co-existence of the non-premixed and premixed combustion regimes complicates the modeling since traditional combustion models are mostly for a single regime. In this work, we examine the effect of multi-regime mixing modeling in the transported filtered density function (FDF) method on the predictions of local extinction and reignition. Predictions of local extinction and reignition remain a challenge for the FDF method despite the progress made in the past. To account for the multi-regime combustion, two different mixing timescale models for non-premixed and premixed combustion are combined. A flame index based on the gradients of fuel and oxidizer is used to define a weighting factor to blend the two mixing timescale models. A turbulent jet non-premixed flame with substantial local extinction, the Sydney piloted jet flame L, is adopted as a test case to examine the performance of the multi-regime model in large-eddy simulation/FDF modeling. It is found that the traditional non-premixed mixing timescale model when combined with the modified Curl mixing leads to global extinction for the Sydney flame L without the presence of the premixed combustion regime. After accounting for the multi-regime combustion with proper detection of the different combustion regimes, the predictions for the flame statistics and the amount of local extinction are significantly improved. Furthermore, it suggests the need of including multi-regime combustion for the predictions of local extinction and re-ignition in turbulent non-premixed combustion configurations.

42 ENGINEERING↗

DOE OSTI2017

Revisiting the Bulge–Halo Conspiracy. I. Dependence on Galaxy Properties and Halo Mass

We carry out a systematic investigation of the total mass density profile of massive (log M{sub star}/M{sub ⊙}≳11.3) early-type galaxies and its dependence on galactic properties and host halo mass with the aid of a variety of lensing/dynamical data and large mock galaxy catalogs. The latter are produced via semi-empirical models that, by design, are based on just a few basic input assumptions. Galaxies with measured stellar masses, effective radii, and Sérsic indices, are assigned, via abundance matching relations, host dark matter halos characterized by a typical ΛCDM profile. Our main results are as follows. (1) In line with observational evidence, our semi-empirical models naturally predict that the total, mass-weighted density slope at the effective radius γ′ is not universal, steepening for more compact and/or massive galaxies, but flattening with increasing host halo mass. (2) Models characterized by a Salpeter or variable initial mass function (IMF) and uncontracted dark matter profiles are in good agreement with the data, while a Chabrier IMF and/or adiabatic contractions/expansions of the dark matter halos are highly disfavored. (3) Currently available data on the mass density profiles of very massive galaxies (log M{sub star}/M{sub ⊙}≳12), with M{sub halo}≳3×10{sup 14} M{sub ⊙}, favor instead models with a stellar profile flatter than a Sérsic one in the very inner regions (r ≲ 3–5 kpc), and a cored NFW or Einasto dark matter profile with median halo concentration a factor of ∼2 or ≲1.3, respectively, higher than those typically predicted by N-body numerical simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1980

Volcanic explosion clouds - Density, temperature, and particle content estimates from cloud motion

Photographic records of 10 vulcanian eruption clouds produced during the 1978 eruption of Fuego Volcano in Guatemala have been analyzed to determine cloud velocity and acceleration at successive stages of expansion. Cloud motion is controlled by air drag (dominant during early, high-speed motion) and buoyancy (dominant during late motion when the cloud is convecting slowly). Cloud densities in the range 0.6 to 1.2 times that of the surrounding atmosphere were obtained by fitting equations of motion for two common cloud shapes (spheres and vertical cylinders) to the observed motions. Analysis of the heat budget of a cloud permits an estimate of cloud temperature and particle weight fraction to be made from the density. Model results suggest that clouds generally reached temperatures within 10 K of that of the surrounding air within 10 seconds of formation and that dense particle weight fractions were less than 2% by this time. The maximum sizes of dense particles supported by motion in the convecting clouds range from 140 to 1700 microns.

Wilson, L.↗

NASA NTRS2014

Creating a Test Validated Structural Dynamic Finite Element Model of the X-56A Aircraft

Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of the Multi Utility Technology Test-bed, X-56A aircraft, is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of the X-56A aircraft. The ground vibration test-validated structural dynamic finite element model of the X-56A aircraft is created in this study. The structural dynamic finite element model of the X-56A aircraft is improved using a model tuning tool. In this study, two different weight configurations of the X-56A aircraft have been improved in a single optimization run. Frequency and the cross-orthogonality (mode shape) matrix were the primary focus for improvement, while other properties such as center of gravity location, total weight, and offdiagonal terms of the mass orthogonality matrix were used as constraints. The end result was a more improved and desirable structural dynamic finite element model configuration for the X-56A aircraft. Improved frequencies and mode shapes in this study increased average flutter speeds of the X-56A aircraft by 7.6% compared to the baseline model.

ground vibration test↗

NASA NTRS2014

Creating a Test-Validated Finite-Element Model of the X-56A Aircraft Structure

Small modeling errors in a finite-element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of the X-56A Multi-Utility Technology Testbed aircraft is the flight demonstration of active flutter suppression and, therefore, in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of the X-56A aircraft. The ground-vibration test-validated structural dynamic finite-element model of the X-56A aircraft is created in this study. The structural dynamic finite-element model of the X-56A aircraft is improved using a model-tuning tool. In this study, two different weight configurations of the X-56A aircraft have been improved in a single optimization run. Frequency and the cross-orthogonality (mode shape) matrix were the primary focus for improvement, whereas other properties such as c.g. location, total weight, and off-diagonal terms of the mass orthogonality matrix were used as constraints. The end result was an improved structural dynamic finite-element model configuration for the X-56A aircraft. Improved frequencies and mode shapes in this study increased average flutter speeds of the X-56A aircraft by 7.6% compared to the baseline model.

ground vibration test↗

DOE OSTI2014

A magnetic particle time-of-flight (MagPTOF) diagnostic for measurements of shock- and compression-bang time at the NIF (invited)

A magnetic particle time-of-flight (MagPTOF) diagnostic has been designed to measure shock- and compression-bang time using D{sup 3}He-fusion protons and DD-fusion neutrons, respectively, at the National Ignition Facility (NIF). This capability, in combination with shock-burn weighted areal density measurements, will significantly constrain the modeling of the implosion dynamics. This design is an upgrade to the existing particle time-of-flight (pTOF) diagnostic, which records bang times using DD or DT neutrons with an accuracy better than ±70 ps [H. G. Rinderknecht et al., Rev. Sci. Instrum. 83, 10D902 (2012)]. The inclusion of a deflecting magnet will increase D{sup 3}He-proton signal-to-background by a factor of 1000, allowing for the first time simultaneous measurements of shock- and compression-bang times in D{sup 3}He-filled surrogate implosions at the NIF.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

The weighted priors approach for combining expert opinions in logistic regression experiments

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration. While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure

In this work, cascading transmission line failures are studied through a dynamical model of the power system operating under fixed conditions. The power grid is modeled as a stochastic dynamical system where first-principles electromechanical dynamics are excited by small Gaussian disturbances in demand and generation around a specified operating point. In this context, a single line failure is interpreted in a large deviation context as a first escape event across a surface in phase space defined by line security constraints. The resulting system of stochastic differential equations admits a transverse decomposition of the drift, which leads to considerable simplification in evaluating the quasipotential (rate function) and, consequently, computation of exit rates. Tractable expressions for the rate of transmission line failure in a restricted network are derived from large deviation theory arguments and validated against numerical simulations. Extensions to realistic settings are considered, and individual line failure models are aggregated into a Markov model of cascading failure inspired by chemical kinetics. Cascades are generated by traversing a graph composed of weighted edges representing transitions to degraded network topologies. Numerical results indicate that the Markov model can produce cascades with qualitative power-law properties similar to those observed in empirical cascades.

Kinetic Monte Carlo, rare events, Cascading Failur↗

DOE OSTI2025

Analytical simulation of meander morphology from equilibrium to long-term evolution: Impacts of channel geometry and vegetation-induced coarsening

This study introduces an innovative approach to modeling meandering river morphology, integrating and investigating the effects of geometric characteristics and vegetation-induced channel coarsening. The developed comprehensive framework combines several advanced techniques: Genetic Programming for refining the scour factor of transverse bed slope, a Leaf Area Index (LAI)-enhanced analytical model for quantifying vegetative flow resistance, and an upstream-weighted moving average method for efficient approximation of the convolution integral in meander migration calculations. The model is validated against both an idealized Kinoshita meander and a natural bend of the Tumen River (China) in equilibrium, demonstrating its robustness across diverse scales and conditions. The model's ability to simulate the long-term evolution, including cutoff events, provides valuable insight for river management strategies. The current findings demonstrate that channel geometry, particularly width-to-depth ratio, plays a dominant role in meander evolution, with wider channels prone to more complex and rapid morphological changes. Vegetation effects are most pronounced in channels with moderate width-to-depth ratios, where they can significantly influence migration rates and bed topography. A combination of channel widening and deepening, coupled with strategic vegetation management, can effectively enhance navigability while maintaining channel stability in the studied Tumen River reach. Sensitivity analyses highlight the complex interplay between hydraulic conditions, sediment characteristics, and vegetation in shaping river morphology. This research advances understanding of the multifaceted nature of meandering river systems and offers practical tools for informed decision-making in river engineering and environmental management, particularly in the context of climate change and increasing anthropogenic pressures on fluvial ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Spike-and-Slab Shrinkage Priors for Structurally Sparse Bayesian Neural Networks

Network complexity and computational efficiency have become increasingly significant aspects of deep learning. Sparse deep learning addresses these challenges by recovering a sparse representation of the underlying target function by reducing heavily overparameterized deep neural networks. Specifically, deep neural architectures compressed via structured sparsity (e.g., node sparsity) provide low-latency inference, higher data throughput, and reduced energy consumption. In this article, we explore two well-established shrinkage techniques, Lasso and Horseshoe, for model compression in Bayesian neural networks (BNNs). To this end, we propose structurally sparse BNNs, which systematically prune excessive nodes with the following: 1) spike-and-slab group Lasso (SS-GL) and 2) SS group Horseshoe (SS-GHS) priors, and develop computationally tractable variational inference, including continuous relaxation of Bernoulli variables. We establish the contraction rates of the variational posterior of our proposed models as a function of the network topology, layerwise node cardinalities, and bounds on the network weights. Furthermore, we empirically demonstrate the competitive performance of our models compared with the baseline models in prediction accuracy, model compression, and inference latency.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Modeling fatigue crack growth in cross ply titanium matrix composites

In this study, the fatigue crack growth behavior of fiber bridging matrix cracks in cross-ply SCS-6/Ti-15-3 and SCS-6/Timetal-21S laminates containing center holes was investigated. Experimental observations revealed that matrix cracking was far more extensive and wide spread in the SCS-6/Ti-15-3 laminates compared to that in the SCS-6/Timetal-21S laminates. In addition, the fatigue life of the SCS-6/Ti-15-3 laminates was significantly longer than that of the SCS-6/Timetal-21S laminates. The matrix cracking observed in both material systems was analyzed using a fiber bridging (FB) model which was formulated using the boundary correction factors and weight functions for center hole specimen configurations. A frictional shear stress is assumed in the FB model and was used as a curve fitting parameter to model matrix crack growth data. The higher frictional shear stresses calculated in the SCS-6/Timetal-21S laminates resulted in lower stress intensity factors in the matrix and higher axial stresses in the fibers compared to those in the SCS-6/Ti-15-3 laminates at the same applied stress levels.

Bakuckas, J. G., Jr.↗

NASA NTRS2022

Earth System Model Parameter Adjustment Using a Green's Functions Approach

We demonstrate the practicality and effectiveness of using a Green's functions estimation approach for adjusting uncertain parameters in an Earth system model (ESM). This estimation approach has previously been applied to an intermediate-complexity climate model and to individual ESM components, e.g., ocean, sea ice, or carbon cycle components. Here, the Green's functions approach is applied to a state-of-the-art ESM that comprises a global atmosphere/land configuration of the Goddard Earth Observing System (GEOS) coupled to an ocean and sea ice configuration of the Massachusetts Institute of Technology general circulation model (MITgcm). Horizontal grid spacing is approximately 110 km for GEOS and 37–110 km for MITgcm. In addition to the reference GEOS-MITgcm simulation, we carried out a series of model sensitivity experiments, in which 20 uncertain parameters are perturbed. These “control” parameters can be used to adjust sea ice, microphysics, turbulence, radiation, and surface schemes in the coupled simulation. We defined eight observational targets: sea ice fraction, net surface shortwave radiation, downward longwave radiation, near-surface temperature, sea surface temperature, sea surface salinity, and ocean temperature and salinity at 300 m. We applied the Green's functions approach to optimize the values of the 20 control parameters so as to minimize a weighted least-squares distance between the model and the eight observational targets. The new experiment with the optimized parameters resulted in a total cost reduction of 9 % relative to a simulation that had already been adjusted using other methods. The optimized experiment attained a balanced cost reduction over most of the observational targets. We also report on results from a set of sensitivity experiments that are not used in the final optimized simulation but helped explore options and guided the optimization process. These experiments include an assessment of sensitivity to the number of control parameters and to the selection of observational targets and weights in the cost function. Based on these sensitivity experiments, we selected a specific definition for the cost function. The sensitivity experiments also revealed a decreasing overall cost as the number of control variables was increased. In summary, we recommend using the Green's functions estimation approach as an additional fine-tuning step in the model development process. The method is not a replacement for modelers' experience in choosing and adjusting sensitive model parameters. Instead, it is an additional practical and effective tool for carrying out final adjustments of uncertain ESM parameters.

Green's Function↗

DOE OSTI2018

Tribological behavior prediction of friction materials for ultrasonic motors using Monte Carlo‐based artificial neural network

ABSTRACT In this article, the relationship of complexity, diversity, and uncertainty between components and tribological properties of friction materials based on a Monte Carlo‐based artificial neural network (MC‐ANN) model was predicted precisely. Meanwhile, the grey relational analysis was applied to figure out weight of factors, optimize formulation design, and calculate nonlinear dependency of ingredients. The accuracy of model was studied by comparing experimental and simulated values on the basis of statistical methods (root‐mean‐squared error). It was found that the model exhibited an excellent performance in predicting and fitting effect. Moreover, comprehensive analysis of weight indicated that nano‐SiO 2 and mica exerted a significant role in improving the friction stability and wear resistance. According to different contents of each ingredient, the corresponding friction coefficient and specific wear rate could be obtained by virtue of a well‐trained MC‐ANN model without experiments, which saved a lot of time and money. It can be expected that the results of this work will extend the current research and pave a route for further in‐depth studies of friction materials. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136 , 47157.

Li, Song↗

DOE OSTI2016

Can We Advance Proton Therapy for Prostate? Considering Alternative Beam Angles and Relative Biological Effectiveness Variations When Comparing Against Intensity Modulated Radiation Therapy

Purpose: For prostate treatments, robust evidence regarding the superiority of either intensity modulated radiation therapy (IMRT) or proton therapy is currently lacking. In this study we investigated the circumstances under which proton therapy should be expected to outperform IMRT, particularly the proton beam orientations and relative biological effectiveness (RBE) assumptions. Methods and Materials: For 8 patients, 4 treatment planning strategies were considered: (A) IMRT; (B) passively scattered standard bilateral (SB) proton beams; (C) passively scattered anterior oblique (AO) proton beams, and (D) AO intensity modulated proton therapy (IMPT). For modalities (B)-(D) the dose and linear energy transfer (LET) distributions were simulated using the TOPAS Monte Carlo platform and RBE was calculated according to 3 different models. Results: Assuming a fixed RBE of 1.1, our implementation of IMRT outperformed SB proton therapy across most normal tissue metrics. For the scattered AO proton plans, application of the variable RBE models resulted in substantial hotspots in rectal RBE weighted dose. For AO IMPT, it was typically not possible to find a plan that simultaneously met the tumor and rectal constraints for both fixed and variable RBE models. Conclusion: If either a fixed RBE of 1.1 or a variable RBE model could be validated in vivo, then it would always be possible to use AO IMPT to dose-boost the prostate and improve normal tissue sparing relative to IMRT. For a cohort without rectum spacer gels, this study (1) underlines the importance of resolving the question of proton RBE within the framework of an IMRT versus proton debate for the prostate and (2) highlights that without further LET/RBE model validation, great care must be taken if AO proton fields are to be considered for prostate treatments.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS2016

Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation

This paper describes an algorithm for atmospheric state estimation based on a coupling between inertial navigation and flush air data-sensing pressure measurements. The navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to estimate the atmosphere using a nonlinear weighted least-squares algorithm. The approach uses a high-fidelity model of atmosphere stored in table-lookup form, along with simplified models propagated along the trajectory within the algorithm to aid the solution. Thus, the method is a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content. The algorithm is applied to the design of the pressure measurement system for the Mars 2020 mission. A linear covariance analysis is performed to assess estimator performance. The results indicate that the new estimator produces more precise estimates of atmospheric states than existing algorithms.

Karlgaard, Christopher D.↗

NASA NTRS1986

Application of multiple objective optimization techniques to finite element model tuning

This report examines tuning a finite element model using vector optimization techniques. Structural models using finite element theory often need to be adjusted so they can accurately simulate the real structure. The goal is to tune the model such that it will reproduce data derived from structural tests. First, the performance indices are extremized using multiple objective optimization theory, producing a set of possible solutions. Next, the solutions are rank ordered according to a decision maker's preferences to select the best answer. The tuning process was applied to a T-38 horizontal stabilizer. Numerous weighted solutions contained a best static deformation model, a best frequency model and three intermediate combinations of these two models. This automated procedure proved to be a versatile method capable of producing solutions for many types of tuning problems.

Devore, Charles R.↗