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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Pyomo.GDP: an ecosystem for logic based modeling and optimization development

We present three core principles for engineering-oriented integrated modeling and optimization tool sets—intuitive modeling contexts, systematic computer-aided reformulations, and flexible solution strategies—and describe how new developments in Pyomo.GDP for Generalized Disjunctive Programming (GDP) advance this vision. We describe a new logical expression system implementation for Pyomo.GDP allowing for a more intuitive description of logical propositions. The logical expression system supports automated reformulation of these logical constraints to linear constraints. We also describe two new logic-based global optimization solver implementations built on Pyomo.GDP that exploit logical structure to avoid “zero-flow” numerical difficulties that arise in nonlinear network design problems when nodes or streams disappear. These new solvers also demonstrate the capability to link to external libraries for expanded functionality within an integrated implementation. We present these new solvers in the context of a flexible array of solution paths available to GDP models. Finally, we present results on a new library of GDP models demonstrating the value of multiple solution approaches.

42 ENGINEERING↗
DOE OSTI2024

Prediction of plant complex traits via integration of multi-omics data

The formation of complex traits is the consequence of genotype and activities at multiple molecular levels. However, connecting genotypes and these activities to complex traits remains challenging. Here, we investigate whether integrating genomic, transcriptomic, and methylomic data can improve prediction for six Arabidopsis traits. We find that transcriptome- and methylome-based models have performances comparable to those of genome-based models. However, models built for flowering time using different omics data identify different benchmark genes. Nine additional genes identified as important for flowering time from our models are experimentally validated as regulating flowering. Gene contributions to flowering time prediction are accession-dependent and distinct genes contribute to trait prediction in different genotypes. Models integrating multi-omics data perform best and reveal known and additional gene interactions, extending knowledge about existing regulatory networks underlying flowering time determination. These results demonstrate the feasibility of revealing molecular mechanisms underlying complex traits through multi-omics data integration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

3D CAD Modeling and Mechanical Integration at the Mu2e Experiment at Fermilab

This abstract encapsulates a transformative summer internship at Fermilab, focusing on the Mu2e Experiment within the Mechanical Integration and 3D CAD Modeling group. The internship was characterized by a two-phase approach, with the initial month dedicated to the design of an aluminum platform tailored for DS Trench Maintenance. This phase encompassed a comprehensive exploration of structural integrity, material selection, and precision engineering principles, demonstrating an adeptness in CAD modeling and a keen eye for detail. The subsequent month saw a seamless transition into a dynamic phase of the project, wherein the intern played a pivotal role in effecting numerous adjustments across diverse sections of the 3D experiment structure. This phase demanded a nuanced understanding of the intricacies of the Mu2e Experiment and a high level of proficiency in CAD modeling.

3D CAD Modeling↗
DOE OSTI2023

Multiphysics Modeling of Hydrokinetic Turbine Energy Conversion System

Hydrokinetic turbines (HKTs) hold great promise as a renewable energy source, but high maintenance costs and limited energy output hinder their widespread adoption. The lack of comprehensive research on HKT drivetrain designs creates a knowledge gap in enhancing generation efficiency and cost reduction. A model of the HKT system with a focus on electric drivetrains and power converters is required to address this knowledge gap. This paper first introduces a MATLAB-averaged model integrating electrical-mechanical-thermal domains and aging behaviors within multi-time frames. Then a PLECS model, which incorporates maximum power point tracking and dq reference framed control for AC-DC-AC power converters, is enriched by a dynamic thermal model to predict fast transients accurately. These models optimize the design at the component level, resulting in improved integrated system performance. Furthermore, the validation of the models is carried out through hardware experiments for the averaged model and hardware-in-the-loop testing for the dynamic model.

ADVANCED PROPULSION SYSTEMS,HYDRO ENERGY↗
DOE OSTI2024

Real-time capable modeling of ICRF heating on NSTX and WEST via machine learning approaches

Abstract A real-time capable core Ion Cyclotron Range of Frequencies (ICRF) heating model on NSTX and WEST is developed. The model is based on two nonlinear regression algorithms, the random forest ensemble of decision trees and the multilayer perceptron neural network. The algorithms are trained on TORIC ICRF spectrum solver simulations of the expected flat-top operation scenarios in NSTX and WEST assuming Maxwellian plasmas. The surrogate models are shown to successfully capture the multi-species core ICRF power absorption predicted by the original model for the high harmonic fast wave and the ion cyclotron minority heating schemes while reducing the computational time by six orders of magnitude. Although these models can be expanded, the achieved regression scoring, computational efficiency and increased model robustness suggest these strategies can be implemented into integrated modeling frameworks for real-time control applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Impacts of elevated temperature on ant species, communities and ecological roles at two temperate forests in Eastern North America

Over the course of five years we have established a long-term array of warming chambers at Duke and Harvard Forest that simulate future conditions with regard to temperature. In these chambers, we have studied, ants, other animal taxa, fungi, bacteria and plants and their responses to the treatments. We have coupled these studies with lab experiments, large-scale observations, and models to contextualize our results. Finally, we have developed integrative models of the future distribution of species and their consequences as a result of warming in eastern North America and more generally.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2012

Impact of Aerosols on Convective Clouds and Precipitation

Aerosols are a critical.factor in the atmospheric hydrological cycle and radiation budget. As a major agent for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosols have a major impact on the dynamics, microphysics, and electrification properties of continental mixed-phase convective clouds. In addition, high aerosol concentrations in urban environments could affect precipitation variability by providing a significant source of cloud condensation nuclei (CCN). Such pollution . effects on precipitation potentially have enormous climatic consequences both in terms of feedbacks involving the land surface via rainfall as well as the surface energy budget and changes in latent heat input to the atmosphere. Basically, aerosol concentrations can influence cloud droplet size distributions, the warm-rain process, the cold-rain process, cloud-top heights, the depth of the mixed-phase region, and the occurrence of lightning. Recently, many cloud resolution models (CRMs) have been used to examine the role of aerosols on mixed-phase convective clouds. These modeling studies have many differences in terms of model configuration (two- or three-dimensional), domain size, grid spacing (150-3000 m), microphysics (two-moment bulk, simple or sophisticated spectral-bin), turbulence (1st or 1.5 order turbulent kinetic energy (TKE)), radiation, lateral boundary conditions (i.e., closed, radiative open or cyclic), cases (isolated convection, tropical or midlatitude squall lines) and model integration time (e.g., 2.5 to 48 hours). Among these modeling studies, the most striking difference is that cumulative precipitation can either increase or decrease in response to higher concentrations of CCN. In this presentation, we review past efforts and summarize our current understanding of the effect of aerosols on convective precipitation processes. Specifically, this paper addresses the following topics: observational evidence of the effect of aerosols on precipitation processes, and results from (CRM) simulations. Note that this presentation is mainly based on a recent paper published in Geophy. Rev. (Tao et al. 2012).

Tao, Wei-Kuo↗
DOE OSTI2016

Drivers of Change in Managed Water Resources: Modeling the Impacts of Climate and Socioeconomic Changes Using the US Midwest as a Case Study

A global integrated assessment model including a water-demand model driven by socio-economics, is coupled in a one-way fashion with a land surface hydrology – routing – water resources management model. The integrated modeling framework is applied to the U.S. Upper Midwest (Missouri, Upper Mississippi, and Ohio) to advance understanding of the regional impacts of climate and socio-economic changes on integrated water resources. Implications for future flow regulation, water supply, and supply deficit are investigated using climate change projections with the B1 and A2 emission scenarios, which affect both natural flow and water demand. Changes in water demand are driven by socio-economic factors, energy and food demands, global markets and prices. The framework identifies the multiple spatial scales of interactions between the drivers of changes (natural flow and water demand) and the managed water resources (regulated flow, supply and supply deficit). The contribution of the different drivers of change are quantified regionally, and also evaluated locally, using covariances. The integrated framework shows that water supply deficit is more predictable over the Missouri than the other regions in the Midwest. The predictability of the supply deficit mostly comes from long term changes in water demand although changes in runoff has a greater contribution, comparable to the contribution of changes in demand, over shorter time periods. The integrated framework also shows that spatially, water demand drives local supply deficit. Using elasticity, the sensitivity of supply deficit to drivers of change is established. The supply deficit is found to be more sensitive to changes in runoff than to changes in demand regionally. It contrasts with the covariance analysis that shows that water demand is the dominant driver of supply deficit over the analysed periods. The elasticity indicates the level of mitigation needed to control the demand in order to reduce the vulnerability of the integrated system in future periods. The elasticity analyses also emphasize the need to address uncertainty with respect to changes in natural flow in integrated assessment.

climate change, water resources management, socio-↗
DOE OSTI2021

Modeling airborne pathogen transport and transmission risks of SARS-CoV-2

An integrated modeling approach has been developed to better understand the relative impacts of different expiratory and environmental factors on airborne pathogen transport and transmission, motivated by the recent COVID-19 pandemic. Computational fluid dynamics (CFD) modeling was used to simulate spatial-temporal aerosol concentrations and quantified risks of exposure as a function of separation distance, exposure duration, environmental conditions (e.g., airflow/ventilation), and face coverings. The CFD results were combined with infectivity models to determine probability of infection, which is a function of the spatial-temporal aerosol concentrations, viral load, infectivity rate, viral viability, lung-deposition probability, and inhalation rate. Uncertainty distributions were determined for these parameters from the literature. Probabilistic analyses were performed to determine cumulative distributions of infection probabilities and to determine the most important parameters impacting transmission. This modeling approach has relevance to both pathogen and pollutant dispersion from expelled aerosol plumes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Dynamic urban land extensification is projected to lead to imbalances in the global land-carbon equilibrium

Abstract Human-Earth System Models and Integrated Assessment Models used to explore the land-atmosphere implications of future land-use transitions generally lack dynamic representation of urban lands. Here, we conduct an experiment incorporating dynamic urbanization in a multisector model framework. We integrate projected dynamic non-urban lands from a multisector model with projected dynamic urban lands from 2015 to 2100 at 1-km resolution to examine 1 st -order implications to the land system, crop production, and net primary production that can arise from the competition over land resources. By 2100, future urban extensification could displace 0.1 to 1.4 million km 2 of agriculture lands, leading to 22 to 310 Mt of compromised corn, rice, soybean, and wheat production. When considering increased corn production required to meet demands by 2100, urban extensification could cut increases in yields by half. Losses in net primary production from displaced forest, grassland, and croplands ranged from 0.24 to 2.24 Gt C yr −1 , potentially increasing land emissions by 1.19 to 6.59 Gt CO 2 yr −1 . Although these estimates do not consider adaptive responses, 1 st -order experiments can elucidate the individual role of sub-sectors that would otherwise be masked by model complexity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Developing integrated parametric planning models for budgeting and managing complex projects

The applicability of integrated parametric models for the budgeting and management of complex projects is investigated. Methods for building a very flexible, interactive prototype for a project planning system, and software resources available for this purpose, are discussed and evaluated. The prototype is required to be sensitive to changing objectives, changing target dates, changing costs relationships, and changing budget constraints. To achieve the integration of costs and project and task durations, parametric cost functions are defined by a process of trapezoidal segmentation, where the total cost for the project is the sum of the various project cost segments, and each project cost segment is the integral of a linearly segmented cost loading function over a specific interval. The cost can thus be expressed algebraically. The prototype was designed using Lotus-123 as the primary software tool. This prototype implements a methodology for interactive project scheduling that provides a model of a system that meets most of the goals for the first phase of the study and some of the goals for the second phase.

Etnyre, Vance A.↗
DOE OSTI2014

Workshop on Modeling and Simulation of Systems and Applications, August 13-14, 2014, University of Washington, Seattle

In our efforts to continue the momentum toward quantitative understanding of the performance, power, and reliability of systems and applications, the modeling and simulation (hereafter ModSim) community gathered for its annual Workshop on Modeling & Simulation of Systems and Applications, held August 13-14, 2014 in Seattle. The 2014 Workshop on Modeling & Simulation of Systems and Applications, or ModSim 2014, focused on three critical technological areas: 1. Integrated Modeling and Simulation of Performance, Power, and Reliability; 2. Standards, Integration, and Interoperability of ModSim Methodologies and Tools; and 3. Advances in Core Modeling and Simulation Methods and Tools. The two-day meeting featured 21 presentations (based on peer-reviewed submissions) delivered over six parallel sessions, and there were six invited talks. Discussions aimed toward consolidating and directing this diverse technical community were especially beneficial as we continue to map out the future and form of ModSim research and development. This report presents a summary of the presentations, discussions, and findings culled from ModSim 2014. Each of the three critical technology areas are presented, structured as major research directions, gaps, cross-pollination, and path forward.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1981

Neutral winds and electric fields in the dust auroral oval. II - Theory and model

A two-dimensional numerical model of the thermosphere is applied to the auroral zone neutral wind, electric field, and plasma density data set, presented in an earlier paper. The model shows that the action of the Lorentz force can be responsible to a great extent for the large zonal velocities near the 150-km altitude. Model equations are described, an explanation of the use of the geophysical conditions is given, and model integrations are compared to the wind measurements. However, for the two-dimensional model to be effective, the atmosphere must not cross too many meridians of local time during the integration period, so that the background state should remain fairly uniform. It is concluded that the two-dimensional model cannot accurately explain the details of the wind profiles because of the three-dimensional character of the physical situation. Thus it is noted that the observed winds were part of a large-scale three-dimensional flow which is only weakly coupled to short-term variations in magnetospheric conditions.

Mikkelsen, I. S.↗
DOE OSTI2026

Multimodal framework for the joint analysis of single-cell RNA and T cell receptor sequencing data predicts T cell response to cancer immunotherapy

T cell states are prognostic in different cancer types. Recent technologies enable joint profiling of T cell RNA and T cell receptor (TCR) sequences at single-cell resolution. Here we present the TCR-RNA Integrating Model (TRIM), a multi-modal variational autoencoder framework that integrates RNA-TCR data and predicts T cell clonality and transcriptional states. TRIM learns a shared representation of the data conditioned on patient, tissue source, and treatment timepoint. We applied TRIM to three independent datasets that included T cells collected before and after checkpoint inhibitor treatment, sourced either from blood and tumor biopsies in patients with head and neck squamous cell carcinoma and colorectal cancer, or from tumor and adjacent tissue in a pan-cancer dataset. In all settings, TRIM accurately predicted intra-tumor T cell clonal expansion and transcriptional status based on T cells from blood or normal tissue before treatment, demonstrating its utility in modeling multimodal T cell data and predicting T cell response to treatment and disease progression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Edge-localized-mode simulation in CFETR steady-state scenario

We report the EPED1 model and self-consistent core-pedestal coupling in integrated modeling are used to design the pedestal structure of the China Fusion Engineering Testing Reactor (CFETR) steady-state scenario. The key parameters, such as β p and q 95 , are based on the grassy edge-localized-mode (ELM) experimental database. In this work, we use the BOUT++ six-field two-fluid code to simulate the onset of the ELM in the CFETR steady-state scenario. The ELM size is around 0.2% in nonlinear simulations, which is in the experimental range of the grassy ELM discharges, 0.1%–1% observed in multiple tokamak devices. Linear and nonlinear simulations show that the dominant high-n ballooning modes peak around n = 40. Compared to type-I ELM crashing dynamics, grassy ELM crashing has a smaller initial crash and is then followed by three phases of turbulence spreading, which are dominated by multi-modes, a high-n mode of n = 45 and low-n mode of n = 5, respectively. In contras to type-I ELM, the perturbation of the high-n mode has a narrow width around ψ = 0.95, and magnetic island formation and reconnection occur only beyond ψ = 0.95, leading to a small initial crash. Mode–mode interaction in the multi-mode coexistence stage stops the growth of individual modes and reduces the transport of particles and heat, and these are the two reasons why the ELM size is small. In–out asymmetry of transient heat flux with a ratio of E out /E in = 3.5 is found during grassy ELM crash. The rise and delay times of the heat flux match the calculation from the free-streaming model. To evaluate the erosion of the divertor target, the energy fluence at the outer divertor target is calculated, which is 0.029 MJ m -2 , 5.5 times smaller than the tungsten melting limit 0.16 MJ m -2 . The calculated energy fluency still follows the experimental scaling law from type-I ELM experiments. The fluctuation eddies in the toroidal direction show a filament structure at the outer mid-plane. Parallel heat flux patterns with a toroidal mode number n = 10 are found at the outer divertor with an amplitude of 680 MW m -2 .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

U-10Mo/Zr Interface Modeling using a Microstructure-Based FEM Approach

The U-10Mo in low enrichments (LEU) has been identified as the most promising alternative to the current highly enriched uranium (HEU) used in the United States’ fleet of high performance research reactors (USHPRRs). The nominal configuration of the new LEU U-10Mo plate fuel comprises a U-10Mo fuel foil enriched to slightly less than 20% U-235 (0.08” to 0.02” thick), a thin Zr interlayer/diffusion barrier (25 m thick) and a relatively thick outer can of 6061 aluminum. Currently, the Zr interlayer is clad by hot roll bonding. Previous studies and observations revealed a thinning of the zirconium (Zr) layer during this fuel fabrication process, which is not desirable from the fuel performance perspective. Coarse UMo grains, dendritic structures, Mo concentration segregation, carbides, and porosity are present in the as-cast material and can lead to a nonuniform UMo/Zr interface. The purpose of the current work is to investigate the effects of these microstructural parameters on the Zr coating variation. A microstructure-based finite-element method model was used in this work, and a study on the effect of homogenization on the interface between U-10Mo and Zr was conducted. The model uses actual backscattered electron–scanning electron microscopy microstructures, Mo concentrations, and mechanical properties to predict the behavior of a representative volume element under compressive loading during the rolling process. The model successfully predicted the experimentally observed thinning of the Zr layer in the as-cast material. The model also uses results from a homogenization model as an input, and a study on the effect of different levels of homogenization on the interface indicated that homogenization helps decrease this thinning. This model can be considered a predictive tool representing a first step for model integration and an input into a larger fuel fabrication performance model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Powered By reV [Slides]

The reV model empowers users to calculate energy capacity, generation, and cost based on geospatial intersection with grid infrastructure and land-use characteristics. The tool can model a single site up to an entire continent at temporal resolutions ranging from five minutes to hourly, spanning a single year or multiple decades. By automating access to resource data at unprecedented scale, fidelity, and flexibility, the reV model integrates formerly disparate analysis frameworks in the fields of resource modeling, technical potential, and energy cost supply curves.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1987

Execution environment for intelligent real-time control systems

Modern telerobot control technology requires the integration of symbolic and non-symbolic programming techniques, different models of parallel computations, and various programming paradigms. The Multigraph Architecture, which has been developed for the implementation of intelligent real-time control systems is described. The layered architecture includes specific computational models, integrated execution environment and various high-level tools. A special feature of the architecture is the tight coupling between the symbolic and non-symbolic computations. It supports not only a data interface, but also the integration of the control structures in a parallel computing environment.

Sztipanovits, Janos↗