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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Multi-Model and Multi-Scale Global Sensitivity Analysis for Identifying Controlling Processes of Complex Systems

An environmental model consists of multiple process level sub-models, and each sub-model represents a process that is key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this project develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods with variance-based global sensitivity analysis to address uncertainty in process models and parameters. The new method yields three process sensitivity indices. The first one is called first-order process sensitivity index, and it is derived as a single summary measure of relative process importance. Evaluating the index is computationally expensive, because it relies in a Monte Carlo scheme that requires thousands and even millions of model executions. To reduce computational cost, this project develops a computationally efficient, quasi Monte Carlo method, and this method is presented in Chapter 2 of this report with and a numerical example for demonstration. The numerical example shows that the results of the quasi Monte Carlo method are substantially close to those of the full Monte Carlo method, but the computational cost of the quasi Monte Carlo method is only 0.7% of that of the full Monte Carlo method. The second index is called total-effect process sensitivity index, and it measures interactions between different processes. Therefore, this sensitivity index includes the first-order process sensitivity index, and can be used to identify influential processes. On the other hand, the total-effect process sensitivity index can also be used to screen non-influential processes. This is demonstrated by two numerical examples using the Sobol-G* functions and groundwater flow models that consider recharge process, geological process, and snowmelt process. The numerical examples shows that the total-effect process sensitivity index is more informative than the first-order process sensitivity. The derivation of the process sensitivity index and the numerical examples are discussed in Chapter 3. Chapter 4 presents two computationally efficient methods for screening non-influential processes to exclude them from further investigation. The two methods are the multi-model difference-based sensitivity (MMDS) analysis method, which can be implemented using the Latin Hypercube Sampling. The second one is the implementation of MMDS method using a binning method. The numerical example for the Sobol-G* function indicates the two methods are capable of identifying non-influential models, and the numerical examples for the groundwater flow and reactive transport show that the two methods are effective for groundwater problems. However, it should be noted that the two methods are numerical approximations, and they can only be used for screening non-influential processes, not for ranking importance of system processes. All the sensitivity analysis methods are implemented by developing python codes, and the codes are in a software called SAMMPY: a python package for process sensitivity analysis under multiple models. The SAMMPY design and structure are discussed in Chapter 5, and the package is released to the public for free download.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Tutorial: Lessons Learned for Behavior Analysts from Data Scientists

Big data is a computing term used to refer to large and complex data sets, typically consisting of terabytes or more of diverse data that is produced rapidly. The analysis of such complex data sets requires advanced analysis techniques with the capacity to identify patterns and abstract meanings from the vast data. The field of data science combines computer science with mathematics/statistics and leverages artificial intelligence, in particular machine learning, to analyze big data. This field holds great promise for behavior analysis, where both clinical and research studies produce large volumes of diverse data at a rapid pace (i.e., big data). This article presents basic lessons for the behavior analytic researchers and clinicians regarding integration of data science into the field of behavior analysis. We provide guidance on how to collect, protect, and process the data, while highlighting the importance of collaborating with data scientists to select a proper machine learning model that aligns with the project goals and develop models with input from human experts. Here, we hope this serves as a guide to support the behavior analysts interested in the field of data science to advance their practice or research, and helps them avoid some common pitfalls.

42 ENGINEERING↗
DOE OSTI2023

Developing an Evolutionary Baseline Model for Humans: Jointly Inferring Purifying Selection with Population History

Building evolutionarily appropriate baseline models for natural populations is not only important for answering fundamental questions in population genetics—including quantifying the relative contributions of adaptive versus nonadaptive processes—but also essential for identifying candidate loci experiencing relatively rare and episodic forms of selection (e.g., positive or balancing selection). Here, a baseline model was developed for a human population of West African ancestry, the Yoruba, comprising processes constantly operating on the genome (i.e., purifying and background selection, population size changes, recombination rate heterogeneity, and gene conversion). Specifically, to perform joint inference of selective effects with demography, an approximate Bayesian approach was employed that utilizes the decay of background selection effects around functional elements, taking into account genomic architecture. This approach inferred a recent 6-fold population growth together with a distribution of fitness effects that is skewed towards effectively neutral mutations. Importantly, these results further suggest that, although strong and/or frequent recurrent positive selection is inconsistent with observed data, weak to moderate positive selection is consistent but unidentifiable if rare.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Enabling off-highway diesel engine downsizing and performance improvement using electrically assisted turbocharging

Internal combustion engine (ICE) downsizing through various turbocharging configurations is generally known by the powertrain design community as an effective means to reduce frictional losses, increase waste heat recovery, and improve fuel efficiency while increasing engine power density. However, often is the case that turbocharging strategies, including variable geometry turbochargers, and regulated two-stage turbochargers, incur the performance tradeoff between transient response and fuel economy (pumping losses) at high engine speeds. For off-highway vehicles having particularly transient and high-powered duty cycles, efforts to improve this tradeoff and increase operational flexibility have turned to evaluating various electrified air system architectures. In this study, a 4.5 L diesel-ICE configured with an electrically driven compressor (eBooster ® ) is placed in series with a conventional turbocharger and integrated into a 48 V mild-hybrid powertrain architecture. The objective of this powertrain configuration is to enable engine downsizing by 34%, replacing the current 6.8 L ICE platform with the hybridized 4.5 L ICE concept. The commercial 1-D simulation software GT-SUITE is used for powertrain system development and system optimization. Development and validation of the GT-SUITE model and air system controls is concurrently supported through experimental data collection. The simulation model development includes using machine learning methods for optimizing exhaust gas dilution, injection timing, and eBooster ® power to improve steady-state and transient brake-specific fuel consumption while minimizing criteria pollutant emissions. It was found that total specific fluid consumption over the standardized non-road transient engine duty cycle could be reduced by 18% over the current 6.8 L engine by using an optimized eBoosted 4.5 L engine. The hybridized 4.5 L engine concept concurrently showed sufficient transient response capability and nearly an order of magnitude reduction in duty cycle total soot production.

25 ENERGY STORAGE↗
DOE OSTI2018

Abstract - Cooperative Research and Development Agreement between Sotacarbo and National Energy Technology Laboratory

The objective of this CRADA between NETL and Sotacarbo is to develop mutual collaboration in the areas of: CFD Modeling for optimization of coal/biomass gasification processes, CO 2 Separation by Membranes, CO 2 -to-Liquids, & CO 2 Sequestration. The CFD modeling and optimization of coal/biomass gasification processes project will bring together NETL’s expertise in the area of computational multiphase flows with Sotacarbo’s expertise in the area of design and operation of coal and biomass gasifiers. The outcome of this collaboration should be validated coal/biomass CFD models, which can assist in design and scale-up studies of gasifiers. There are several gasification units at Sotacarbo’s Research Center which can be used for gasification model development and validation using NETL’s MFiX Suite of multiphase flow CFD software. The other remaining technical topic outcomes will be determined at a later time as a result of further discussions.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Multiple Degradation Mechanisms in Reinforced Concrete Structures, Modeling and Risk Analysis

The overarching goal of this project is to complement ongoing Department of Energy (DOE) Light Water Reactor Sustainability (LWRS)-funded Grizzly concrete modeling development efforts by providing improved multi-physics models for incorporation into the Grizzly and BlackBear codes. Objectives of this work identified at the outset of this project include: 1. Coupling between mechanical damage and transport processes. The mechanical damage will be characterized by nonlinear mechanical constitutive models appropriate for concrete used in nuclear power plants (NPPs). 2. Improved representation of the coupling among the transport process, building on the current moisture and thermal transport models in Grizzly. The parameters for coupling among heat and mass transport in the multi-physics model will be experimentally determined. 3. Coupling among different scale levels of concrete constituents, fine and coarse aggregates, cement paste, hydration products, and pore structure. 4. Probabilistic analysis of the random nature of the heterogeneous concrete structure and the environmental factors (ambient temperature and humidity) and their multiple effects on concrete deterioration. 5. Benchmark verification, validation and uncertainty quantification of the thermo-hygro- chemo-mechanical (THCM) concrete formulation. The end goal of this work was to provide a comprehensive and robust simulation capability that can be applied at the engineering scale for analysis of realistic deterioration scenarios in NPP concrete structures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

LANL Institutional Computing Close-out Report for Project t22_ocean_time_step

This year, my team made a very productive use of LANL IC time. Four papers were published that used IC resources, and two more are under review. These publications fall into three categories: 1.) Improving tide modeling in the global ocean by adding self attraction and loading (Barton et. al. 2022), ice shelf cavities (Pal et al. 2023), and local time stepping (Lilly et al. 2023). 2.) A new sea ice numerical formulation (Capodaglio 2023). 3.) Performance comparisons, methods, and test cases for ocean model development, This includes a verification suite for ocean models (Bishnu, submitted) and a comparison between Julia and Fortran (Strauss, submitted). A new time-stepping method was introduced in Calandrini et al. (2022). These publications, and the use of LANL IC resources, go hand-in-hand with our mentoring efforts to train young scientists. Two of the lead authors are graduate students who are conducting their PhD research: Kristin Barton at the University of Michigan and Jeremy Lilly at Oregon State. These are both their first publications, and they both have DOE funding and DOE mentors. In addition, Bishnu is a post-doctoral researcher at LANL; Strauss conducted his research as a senior in high school; and Capodaglio, Calandrini and Pal are all early-career scientists who were converted to staff in 2021 or 2022. Here we highlight two publications on improvements in tidal modeling: Barton et al. 2022 and Lilly et al. 2023.

58 GEOSCIENCES↗
DOE OSTI2022

Consensus DOE Advanced Fuels Campaign TREAT/SATS Test Plan [Slides]

This record is comprised of summary slides of the Combined TREAT-LOC & SATS Integral LOCA Experiment Plan. The experimental program has been developed to specifically address data gaps and opportunities identified through detailed review of the existing public knowledgebase on LOCA FFRD and specific experimental development for prototypic LOCA conditions for LWR systems. The test program relies on a unique combination of in-pile and out-of-pile experimental approaches to (1) provide clear tieback to the existing integral and semi-integral LOCA experiment database using state-of-the-art facilities. More importantly, this program will systematically investigate the impacts of: (2) prototypic HBu fuel and cladding thermomechanical behaviors under postulated LWR LOCA conditions never fully investigated before. These conditions correspond with prototypic decay-energy heat up (DEH) and stored-energy heat up (SEH) conditions. Unique TREAT capability will provide first evaluation of SEH conditions on HBu fuels. The test program includes an emphasis on developing improved mechanistic understanding of key phenomena through independent experimental systems, development of a database to support fuel performance modeling tools, world leading advanced materials characterization, and the most advanced approach to in-situ diagnostics ever deployed to evaluate FFRD. The results will represent a significant leap forward in the evaluation of prototypic conditions and novel data to support modeling development and validation, as well as to inform the technical basis of LOCA-induced FFRD.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Viscoelastic Modeling of Polymers in ALEGRA with the GAP Model

The Glassy Amorphous Polymer (GAP) model is a viscoelastic/plastic model developed at Los Alamos National Laboratory to accurately model a variety of polymers across a wide range of conditions and loading rates, including shock loading. In the present report we introduce and assess this model, newly implemented in the ALEGRA shock and multiphysics code, using a series of verification and application-related validation problems. We describe the mathematical and theoretical formulation of the model, as well as its implementation in ALEGRA, in detail. We provide verification results that assess the model implementation against published computational results, as well as validation results which we compare to existing experimental results when possible. These comparisons instill confidence in the implementation and indicate that the addition of the GAP model to the ALEGRA code provides users with a high-fidelity polymer modeling capability that is capable of recreating complex polymer phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Summary of Responses to the Request for Information (RFI) on Partnerships for Transformational Artificial Intelligence Models

The Department of Energy (DOE) issued a Request for Information (RFI) in December 2025 inviting public comments regarding partnerships for transformational Artificial Intelligence (AI) models for the Genesis Mission Consortium, a public-private partnership platform. This RFI solicited feedback from industry, nonprofit organizations, universities, independent research organizations and other stakeholders. Specifically, the RFI asked three questions on (1) mobilizing DOE National Laboratories to curate the scientific data in a responsible and privacy-preserving manner, (2) the extent to which existing general-purpose AI models can be leveraged and which scientific disciplines are priorities for such model development, and (3) mechanisms by which these AI models can be provided to scientific communities. This document summarizes the input from 194 unique nonproprietary responses from businesses, universities, nonprofit organizations, research institutes and laboratories as well as a variety of other contributors, including individual contributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Rate Theory Model of Radiation-Induced Swelling in an Austenitic Stainless Steel

Many rate theory models of cavity (void) swelling have been published over the past 50 years, all having the same, or similar, structures. A rigorous validation of the models has not been possible because of the dearth of information concerning the microstructures that correspond with the swelling data. Whereas the lack of microstructure information is still an issue for historical swelling data, in the past 10–20 years data have been published on the evolution of the microstructure (point defect yields from collision cascades, cavity number densities, and dislocation densities/yield strengths) allowing certain gaps in information to be filled when considering historic swelling data. With reasonable estimates of key microstructure parameters, a standard rate theory model can be applied, and the model parameter space explored, in connection with historical swelling data. By using published data on: (i) yield strength as a function of dose and temperature (to establish an empirical expression for dislocation density evolution); (ii) cavity number densities as a function of temperature; and (iii) freely migrating defect (FMD) production as a function of primary knock-on atom (PKA) spectrum, the necessary parameter and microstructure inputs that were previously unknown can be used in model development. This paper describes a rate-theory model for void swelling of 316 stainless steel irradiated in the EBR-2 reactor as a function of irradiation temperature and neutron dose.

36 MATERIALS SCIENCE↗
NASA NTRS1976

Second-order closure analysis of turbulent reacting flows

A reacting shear layer program for a complete second-order closure of turbulent reacting flows is developed. The program uses a typical eddy box model and many of the fluid mechanical turbulence models developed in earlier studies. The computer program actually solves a total of 30 equations, where the numerical integration of the equations is performed by a forward-time-centered space quasi-implicit upwind finite-difference scheme. Results for nonreacting and simple isothermal reacting flows are presented along with preliminary results for propane-air flames. It is shown that the program predictions for simple nonreacting flows are in good agreement with available data. The calculations for isothermal reacting flows demonstrate the importance of including a mixedness correlation in finite rate chemistry calculations, where significant errors in the flowfield properties can result from neglect of the interaction between turbulence and the chemistry. Results for propane-air diffusion flames further support this conclusion.

Varma, A. K.↗
NASA NTRS1979

On turbulence modeling for unsteady transonic flows

A detailed examination of the turbulent field in an unsteady transonic flow undergoing shock-induced separation is conducted. Ensemble-averaged mean and fluctuating velocities, obtained from conditionally sampled laser velocimeter data, are described and analyzed to assess the applicability of modeling concepts usually employed in steady-flow problems. Some comparisons with computations employing the Reynolds averaged Navier-Stokes equations with a mixing length turbulence model are then presented to illustrate the status of current predictive capabilities. The results appear to imply that turbulence models developed for steady flows apply and that the model need not reflect all the fine details of the turbulent structure but rather account in an approximate way for the production and destruction of the turbulence.

Marvin, J. G.↗
NASA NTRS1987

Aeroelastic modeling of swept tip rotor blades using finite elements

A special finite element for the modeling of a swept tip rotor blade is derived. The swept tip blade undergoes moderate deflections in flap, lag and torsion. The nonlinear, partial differential equations of motion are discretized using a Galerkin finite element method. Tip sweep introduces flap-torsion and lag-axial couplings, and may lead to aeroelastic instabilities associated with frequency coalescence. When frequency coalescence does not occur, sweep is usually stabilizing. A comparison of the approximate model of a swept tip blade, using a blade with straight elastic axis and offsets of aerodynamic centers of gravity, with the exact swept tip model developed in this paper indicates that the approximate model can produce inaccurate results for the case of hingeless rotor blades.

Celi, R.↗
NASA NTRS1992

Modeling the seasonal variability of a coupled Arctic ice-ocean system

The seasonal variability of the ice-ocean system in the Arctic Basin and the Norwegian, Greenland, and Barents Seas was modeled using a three-dimensional coupled ice-ocean model developed at Princeton University. The snow-ice model uses a three-level thermodynamic scheme similar to Semtner's (1976), but is extended to include the effect of leads. It is shown that simulations using the climatological monthly forcing fields produce a realistic seasonal variability of the ice cover. The ice thickness had a considerable sensitivity to the choice of the long-wave back radiation scheme, but these effects can be reduced through dynamical factors.

Hakkinen, Sirpa↗
NASA NTRS1994

Truss structure tele-manipulation experiment using ETS-7

A robot experiment concept of space truss telemanipulation by National Aerospace Laboratory (NAL) is described in its flight model development. The experiment will be carried out on the Engineering Test Satellite No. 7 (ETS-7) using its robot arm. The satellite is scheduled to be launched in 1997 by National Space Development Agency of Japan (NASDA). The truss flight model is composed of deployable truss system and assemble truss joint. Those truss components will be manipulated by the ETS-7 robot arm using its small grapple fixture type-N (GPF-N), and the experimental task operation will be executed from the ground control station.

Matsumoto, Kohtaro↗
NASA NTRS1995

Investigation of Strain Aging in the Ordered Intermetallic Compound beta-NiAl

The phenomenon of strain aging has been investigated in polycrystalline and single crystal NiAl alloys at temperatures between 300 and 1200 K. Static strain aging studies revealed that after annealing at 1100 K for 7200 s (i.e., 2h) followed by furnace cooling, high purity, nitrogen-doped and titanium-doped polycrystalline alloys exhibited continuous yielding, while conventional-purity and carbon-doped alloys exhibited distinct yield points and Luders strains. Prestraining by hydrostatic pressurization removed the yield points, but they could be reintroduced by further annealing treatments. Yield points could be reintroduced more rapidly if the specimens were prestrained uniaxially rather than hydrostatically, owing to the arrangement of dislocations into cell structures during uniaxial deformation. The time dependence of the strain aging events followed at t(exp 2/3) relationship suggesting that the yield points observed in polycrystalline NiAl were the result of the pinning of mobile dislocations by interstitials, specifically carbon. Between 700 and 800 K, yield stress plateaus, yield stress transients upon a ten-fold increase in strain rate, work hardening peaks, and dips in the strain rate sensitivity (SRS) have been observed in conventional-purity and carbon-doped polycrystals. In single crystals, similar behavior was observed; in conventional-purity single crystals, however, the strain rate sensitivity became negative resulting in serrated yielding, whereas, the strain rate sensitivity stayed positive in high purity and in molybdenum-doped NiAl. These observations are indicative of dynamic strain aging (DSA) and are discussed in terms of conventional strain aging theories. The impact of these phenomena on the composition-structure-property relations are discerned. Finally, a good correlation has been demonstrated between the properties of NiAl alloys and a recently developed model for strain aging in metals and alloys developed by Reed-Hill et al.

Weaver, Mark Lovell↗