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Results for “functional modeling”

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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Cortical cell size regulates root metabolic cost

SUMMARY It has been hypothesized that vacuolar occupancy in mature root cortical parenchyma cells regulates root metabolic cost and thereby plant fitness under conditions of drought, suboptimal nutrient availability, and increased soil mechanical impedance. However, the mechanistic role of vacuoles in reducing root metabolic cost was unproven. Here we provide evidence to support this hypothesis. We first show that root cortical cell size is determined by both cortical cell diameter and cell length. Significant genotypic variation for both cortical cell diameter (~1.1‐ to 1.5‐fold) and cortical cell length (~ 1.3‐ to 7‐fold) was observed in maize and wheat. GWAS and QTL analyses indicate cortical cell diameter and length are heritable and under independent genetic control. We identify candidate genes for both phenes. Empirical results from isophenic lines contrasting for cortical cell diameter and length show that increased cell size, due to either diameter or length, is associated with reduced root respiration, nitrogen content, and phosphorus content.RootSlice, a functional‐structural model of root anatomy, predicts that an increased vacuolar: cytoplasmic ratio per unit cortical volume causes reduced root respiration and nutrient content. Ultrastructural imaging of cortical parenchyma cells with varying cortical diameter and cortical cell length confirms thein silicopredictions and shows that an increase in cell size is correlated with increased vacuolar volume and reduced cytoplasmic volume. Vacuolar occupancy and its relationship with cell size merits further investigation as a phene for improving crop adaptation to edaphic stress.

Plant Sciences↗
DOE OSTI2021

Mixture density network estimation of continuous variable maximum likelihood using discrete training samples

Abstract Mixture density networks (MDNs) can be used to generate posterior density functions of model parameters $$\varvec{\theta }$$ θ given a set of observables $${\mathbf {x}}$$ x . In some applications, training data are available only for discrete values of a continuous parameter $$\varvec{\theta }$$ θ . In such situations, a number of performance-limiting issues arise which can result in biased estimates. We demonstrate the usage of MDNs for parameter estimation, discuss the origins of the biases, and propose a corrective method for each issue.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

SWARM: Reimagining scientific workflow management systems in a distributed world

Modern scientific workflows process massive amounts of data from diverse instruments and sensors, leveraging geographically distributed, heterogeneous compute and storage resources—from leadership-class systems to edge devices—connected by high-performance networks. The diversity of resources introduces challenges in harnessing their full potential, with resilience issues arising across applications, system software, networks, storage, and hardware. Today, workflow management systems (WMS) coordinate the execution of computation and data management tasks across target resources. However, WMS’s centralized nature makes them vulnerable to faults and scalability issues that may result in failures of entire computational campaigns. In conclusion, this paper introduces a novel agentic framework for workflow management, fully distributing and decentralizing the WMS functions and modeling them as swarm intelligence agents infused with advanced artificial intelligence solutions and traditional distributed computing algorithms that can make coordinated decisions in the presence of failures of the underlying cyberinfrastructure.

Swarm intelligence↗
DOE OSTI2026

1999 Puget Sound Household Travel Survey

The 1999 Puget Sound Household Travel Survey was conducted between July and November. NuStats Research and Consulting conducted the survey on behalf of the Puget Sound Regional Council. The purpose of the study was to provide data to continue developing and refining the Regional Travel Demand Forecasting Model, as well as to provide a better understanding of travel behavior in the Puget Sound region. The study area consists of King, Kitsap, Pierce, and Snohomish counties. The resultant dataset will be used to fulfill the model's functions of estimating trip generation and distribution, mode choice, and assignments. The study had household members 16 years old or older keep track of travel for a 48-hour period. A total of 9,028 households were recruited to participate in the study. Of these, 6,000 households (66.5%) completed travel diaries, and the information was retrieved from all household members regardless of age. An “attitude” survey about transportation and land use issues was also mailed to household members 16 years old or older.

1Hz data↗
DOE OSTI2026

1998/99 Thurston County Household Travel Study

The survey was conducted under the auspices of the Thurston Regional Planning Council, and it was funded through a state grant awarded to Intercity Transit of Olympia, Washington. Data collection was from September 1998 through March 1999. The purpose of the study was to provide data for the continuing development and refinement of the Regional Travel Demand Forecasting Model, as well as to provide a better understanding of travel behavior in the southern Puget Sound region of Washington. The resultant data set will be used to fulfill the model's functions of estimating trip generation and distribution, mode choice, and assignments. Participating households were assigned specific “travel days” to record their travel over a 48-hour period. A total of 2,465 households were recruited to participate in the study. Of these, 1,537 households completed travel diaries, and the information was retrieved from 3,653 household members regardless of age. Households member made 25,278 total trips during their 48-hour diary period.

1Hz data↗
DOE OSTI2025

popclass: A Python Package for Classifying Microlensing Events

popclass is a Python package that provides a flexible, probabilistic framework for classifying the lens of a gravitational microlensing event. Gravitational microlensing occurs when a massive foreground object (e.g., a star, white dwarf or black hole) passes in front of and lenses the light from a distant background source. This causes an apparent brightening, and shift in position, of the background source. In most cases, characteristics of the microlensing signal do not contain enough information to definitively identify the lens type. Different lens types lie in different but overlapping regions of the characteristics of the microlensing signal. For example, black holes tend to be more massive than stars and therefore cause microlensing signals that are longer. Current Galactic simulations enable us to predict where different lens types lie in the observational space and can therefore be used to classify events (e.g., Lam et al., 2020). popclass allows the user to match the characteristics of a microlensing signal with a simulation of the Galaxy to calculate lens type probabilities for the event (see Figure 1). Constraints on any microlensing signal properties and any Galactic model can be used. popclass comes with an interface to ArviZ (Kumar et al., 2019) and PyMultiNest (Buchner et al., 2014) for microlensing signal constraints, as well as pre-loaded Galactic models, plotting functionality, and methods to quantify the classification uncertainty. The probabilistic framework for popclass was developed in Perkins et al. (2024), used in Fardeen et al. (2024) and has been applied to classifying events in Kaczmarek et al. (2025).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Angle of Incidence Characterization of Six Laminated Solar Cells for 2020 DTU Fotonik Inter-Laboratory Comparison Study

Photovoltaic energy prediction models include functions or modifiers to account for sun angle reflection losses. These functions may be known interchangeably as Angle of Incidence (AOI) or Incident Angle Modifier (IAM). While standards exist, there is no universally accepted single best practice for developing these functions. They can be generated through characterization of representative modules or single cells, in natural sunlight or indoors using simulated light sources. Repeatability of measurements and the viability of cross-laboratory comparisons are critical to confidence in validation of both methods. To investigate the differences between methods and labs, The Technical University of Denmark (DTU) initiated an international round-robin test comparison between several key test labs with AOI measurement capability. A total of six minimodules were provided in three different cell/interconnect/backsheet combinations. Sandia characterized these minimodules using methods developed over two decades specifically for the outdoor characterization of full-size photovoltaic modules. This report documents the characterization results, summarizes key observations and tabulates the processed data for comparison to results provided by other characterization labs.

14 SOLAR ENERGY↗
DOE OSTI2021

An Integrated Feasibility Study of Reservoir Thermal Energy Storage (RTES) in Portland, OR, USA

In regions with long cold overcast winters and sunny summers, Deep Direct-Use (DDU) can be coupled with Reservoir Thermal Energy Storage (RTES) technology to take advantage of pre-existing subsurface permeability to save summer heat for later use during cold seasons. Many aquifers worldwide are underlain by permeable regions (reservoirs) containing brackish or saline groundwater that has limited beneficial use due to poor water quality. We investigate the utility of these relatively deep, slow flowing reservoirs for RTES by conducting an integrated feasibility study in the Portland Basin, Oregon, USA, developing methods and obtaining results that can be widely applied to RTES systems elsewhere. As a case study, we have conducted an economic and social cost-benefit analysis for the Oregon Health and Science University (OHSU), a teaching hospital that is recognized as critical infrastructure in the Portland Metropolitan Area. Our investigation covers key factors that influence feasibility including 1) the geologic framework, 2) heat and fluid flow modeling, 3) capital and maintenance costs, 4) the regulatory framework, and 5) operational risks. By pairing a model of building seasonal heat demand with an integrated model of RTES resource supply, we determine that the most important factors that influence RTES efficacy in the study area are operational schedule, well spacing, the amount of summer heat stored (in our model, a function of solar array size), and longevity of the system. Generally, heat recovery efficiency increases as the reservoir and surrounding rocks warm, making RTES more economical with time. Selecting a base-case scenario, we estimate a levelized cost of heat (LCOH) to compare with other sources of heating available to OHSU and find that it is comparable to unsubsidized solar and nuclear, but more expensive than natural gas. Additional benefits of RTES include energy resiliency in the event that conventional energy supplies are disrupted (e.g., natural disaster) and a reduction in fossil fuel consumption resulting in a smaller carbon footprint. Key risks include reservoir heterogeneity and a possible reduction in permeability through time due to scaling (mineral precipitation). Lastly, a map of thermal energy storage capacity for the Portland Basin yields a total of 43,400 GWh, suggesting tremendous potential for RTES in the Portland Metropolitan Area.

14 SOLAR ENERGY↗
DOE OSTI2021

3D orthorhombic earth model effects on seismic source characterization

Most earth materials are anisotropic with regard to seismic wave-speeds, especially materials such as shales, or where oriented fractures are present. However, the base assumption for many numerical simulations is to treat earth materials as isotropic media. This is done for simplicity, the apparent weakness of anisotropy in the far field, and the lack of well-characterized anisotropic material properties for input into numerical simulations. One approach for addressing the higher complexity of actual geologic regions is to model the material as an orthorhombic medium. We have developed an explicit time-domain, finite-difference (FD) algorithm for simulating three-dimensional (3D) elastic wave propagation in a heterogeneous orthorhombic medium. The objective of this research is to investigate the errors and biases that result from modeling a non-isotropic medium as an isotropic medium. This is done by computing “observed data” by using synthetic, anisotropic simulations with the assumption of an orthorhombic, anisotropic earth model. Green’s functions for an assumed isotropic earth model are computed and then used an inversion designed to estimate moment tensors with the “observed” data. One specific area of interest is how shear waves, which are introduced in an anisotropic model even for an isotropic explosion, affect the characterization of seismic sources when isotropic earth assumptions are made. This work is done in support of the modeling component of the Source Physics Experiment (SPE), a series of underground chemical explosions at the Nevada National Security Site (NNSS).

58 GEOSCIENCES↗
DOE OSTI2022

Evaluation of Oak Ridge National Laboratory Health Physics Research Reactor Operation Data for Critical Benchmark Creation [Slides]

During the evaluation of Oak Ridge National Laboratory Health Physics Research Reactor operation data for critical benchmark creation, a detailed, functional SCALE model was built, and experimental data was evaluated for the creation of a critical benchmark. The estimated experimental uncertainty is about 3800 pcm, which is considered very high. The relative difference between expected and calculated keff values is about 1.5 %, also considered very high. It was concluded that a good quality critical benchmark worthy of the ICSBEP standards cannot be created from HPRR data in the present conditions. Locating the HPRR fuel to obtain an uncertainty on the density would aid in solving this issue.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Experiments for SINBAD: Evaluation of Oak Ridge Health Physics Research Reactor Operation Data for CAAS Benchmark Creation [Slides]

This report was a real information preservation and dissemination work with a lot of legacy content that was found and used. There was an abundance of uncertainty, discrepancy, and contradictory information. Yet, a detailed, functional SCALE model was built, and the benchmark created is useful for shielding and CAAs validation work. Sulfur fluence C/E ratios are large (2 to 5), so different benchmark metrics were studied. Neutron fluence, element 57 dose, and other dosimetry responses at 3 meters C/E ratios are below 1.5 for bare and steel configurations. Additional promising metrics as dose per unit fluence and steel shield attenuation were computed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Task 12 Sustainability - Methodological Guidelines on Net Energy Analysis of Photovoltaic Electricity (2nd Edition)

Net Energy Analysis (NEA) is a structured, comprehensive method of quantifying the extent to which a given energy source is able to provide a net energy gain (i.e., an energy surplus) to the end user, after accounting for all the energy losses occurring along the chain of processes that are required to exploit it (i.e., for its extraction, processing and transformation into a usable energy carrier, and delivery to the end user), as well as for all the additional energy 'investments' that are required in order to carry out the same chain of processes. However, this general framework leaves the individual practitioner with a range of choices that can affect the results and thus, the conclusions of a NEA study. The current IEA PVPS guidelines were developed to provide guidance on assuring consistency, balance, and quality to enhance the credibility and reliability of the results from photovoltaic (PV) NEAs. The guidelines represent a consensus among the authors - PV NEA experts in North America and Europe - for assumptions made on PV performance, process inputs and outputs, methods of analysis, and reporting of the results. Guidance is given on photovoltaic-specific parameters used as inputs in NEA and on choices and assumptions in inventory data analysis and on implementation of modelling approaches. A consistent approach towards system modelling, the functional unit, the system boundaries and allocation aspects enhance the credibility of PV electricity NEA studies and enables balanced NEA-based comparisons. Specifically, "apples-to-oranges" comparisons of different energy carriers (e.g., fuels vs. electricity) are not methodologically sound and are to be avoided in all cases; also, any comparison across renewable and non-renewable electricity generation technologies must clearly point out the intrinsically short-term nature of the NEA viewpoint, which does not capture the long-term sustainability implications of renewable vs. non-renewable primary energy harvesting and use: non-renewable primary energy resources are depleted and finally exhausted (irrespective of the size of the EROI), while renewable primary energy resources are not. This document provides an in-depth discussion of a common metric of NEA, namely the energy return on investment (EROI), and how this is to be interpreted vis-a-vis the deceptively similar-sounding metrics in the field of Life Cycle Assessment (LCA): cumulative energy demand (CED) and non-renewable cumulative energy demand (nr-CED) per unit output. Specifically, a number of key differences are highlighted between these metrics as applied to electricity production systems, which are listed in Table S-1.

14 SOLAR ENERGY↗
DOE OSTI2025

Data for: Subsurface Interface Structure Controlling Local Electronic Properties of Epitaxial Graphene on SiC(0001)

Recently realized high-mobility semiconducting epitaxial graphene on silicon carbide, provided an important step towards integration of the graphene-based system into active components in post-silicon micro- and nano-electronics. However, the exact atomic-scale structure and the complex bonding configurations of the first epitaxial graphene carbon layer remain an open problem. Our recent report has shed new light on understanding this interface, where the external transverse electric field-dependent dynamic switching behavior of the Cbuffer-SiC bonds was observed. Here, using scanning tunneling microscopy and spectroscopy (STM and STS), we present the direct evidence of silicon (Si) vacancies at the interface and provide their distribution at the topmost reconstructed SiC(0001) layer. Experimental STM and density functional theory modeling data were used in the preparation of figures in a published article in the Journal of Physical Chemistry Letters. Files related to the figures and supplementary materials in the article are present in this dataset in .txt format.

Condensed matter imaging↗
DOE OSTI2025

Data for: Subsurface Interface Structure Controlling Local Electronic Properties of Epitaxial Graphene on SiC(0001)

Recently realized high-mobility semiconducting epitaxial graphene on silicon carbide, provided an important step towards integration of the graphene-based system into active components in post-silicon micro- and nano-electronics. However, the exact atomic-scale structure and the complex bonding configurations of the first epitaxial graphene carbon layer remain an open problem. Our recent report has shed new light on understanding this interface, where the external transverse electric field-dependent dynamic switching behavior of the Cbuffer-SiC bonds was observed. Here, using scanning tunneling microscopy and spectroscopy (STM and STS), we present the direct evidence of silicon (Si) vacancies at the interface and provide their distribution at the topmost reconstructed SiC(0001) layer. Experimental STM and density functional theory modeling data were used in the preparation of figures in a published article in the Journal of Physical Chemistry Letters. Files related to the figures and supplementary materials in the article are present in this dataset in .txt format.

Condensed matter imaging↗