Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “gap”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Design Heating and Cooling Load Calculation Versus Building Load Simulation for Cold Climate Heat Pumps: Understanding the "Gap"

This report explores the differences between Manual J-equivalent block load calculations and building HVAC energy simulation results using EnergyPlus™ calculations when designing cold climate heat pump systems for residential use. This study will help HVAC researchers and advanced designers understand the impacts of oversizing heat pumps on home energy use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Ultra-High-Speed X-ray Tomography: Bridging the Gaps to See the Unknown

Rapid, time-varying, three-dimensional physics underpin numerous engineering challenges. Often, these physics occur within opaque environments, internal to a component, severely limiting applicable diagnostics. Development of novel diagnostics is necessary to understand and predict transient three-dimensional (3D) phenomena within opaque environments. This report highlights progress in four key areas leading to advancements in high-speed X-ray radiography and tomography. The first area is enabling MHz-rate imaging of energetics at the Advanced Photon Source at Argonne National Laboratory. The second is modeling a high-flux, rotating-anode X-ray source to understand the heat loads on the anode. The third effort was to develop a novel reconstruction algorithm that is validated by ground experimental tomography data and synthetic tomography data. The fourth is the development of a novel approach to two-color X-ray imaging.

42 ENGINEERING↗
DOE OSTI2023

Software Quality Assurance, Software Requirements and Gap Analysis for the MOOSE-Based Open-Source Multiphysics Code Cardinal

Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on maintaining and enhancing Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework. To facilitate compliance with SQA standards, the Cardinal SQA Program has been initiated during Fiscal Year 2023 (FY23).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Genomes to ecosystem function: Targeting critical knowledge gaps in methanogenesis and translation to updated global biogeochemical models

Natural freshwater temperate wetland systems currently represent the largest natural source of atmospheric methane, but are relatively understudied using systems biology tools (e.g. meta-omics) compared to other high producing methane systems (e.g. peat, tropical, or reconstructed wetlands). Using field investigations at the NOAA operated sentinel site on Lake Erie, methane producing activities and responses to geochemical conditions will be determined along seasonal and spatial gradients (Objective 1). Here, a combination of high-throughput activity and gas measurements, combined with high-resolution systems biology and analytical methods, will provide in depth knowledge of the microbiological, chemical, and physical constraints on methane production in wetlands. Using laboratory microcosms, the formation of anoxic microsites and their capacity to facilitate methane production in wetland soils will be simulated (Objective 2). This objective will validate the findings from the field investigations, offering a more controlled environment for teasing out the role of different yet interrelated variables. Lastly, these field and laboratory data will be used for multi-scale, process-level evaluation of an ecosystem biogeochemical model that accommodates these newly identified processes and parameterizes representation of these processes along relevant environmental gradients (Objective 3).This research will identify multiple interacting geochemical, ecological, and metabolic constraints that are poorly understood, oversimplified, or missing in global biogeochemical methane models. This proposal targets the role of oxygen limitation on methane processes in soil domains, to improve reactive transport models of microbial carbon cycling across terrestrial-aquatic soils and generate data on nutrient cycling activities in Great Lake wetlands. This information could provide new insights into the microbial controllers of Lake Erie eutrophication.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Bridging the Gap on Data, Metrics, and Analyses for Grid Resilience to Weather Events: Information that utilities can provide regulators, state energy offices, and other stakeholders

A growing number of states require regulated utilities to file resilience plans to improve the electric grid’s ability to anticipate, withstand, adapt to and recover from increasingly severe weather events. This report aims to help state regulators identify and request data, metrics, and analyses from utilities and use it in decisions on utility resilience plans and investments. The report reviews state requirements and utility plans focused on overall grid resilience, climate change resilience and vulnerabilities, infrastructure modernization, storm protection, and wildfire mitigation. It details types of data, metrics, and analyses across five categories--and provides examples of each from the utility plans. The first category is vulnerability assessments, or evaluations of the susceptibility of systems, communities, or assets to potential harm from identified hazards. The second is data on hazards and the exposure of utility assets and customers to these hazards. The third is attribute metrics, or system characteristics that contribute to or describe the resilience of a system. The fourth is performance metrics, which are impacts of resilience investments on system performance--typically a reduction of negative impacts from hazard events. Finally, evaluation and prioritization are analyses that utilities conduct to estimate impacts from resilience measures (evaluation) and prioritize measures based on costs and estimated impacts (prioritization). The report concludes with examples of key trends and emerging best practices for states and utilities, and identifies areas for further research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Bridging the Gap Between Pure and Mixed-Gas Performance of Thin-Film Composite Membranes

This study examines the influence of cell design on mixed-gas testing with PolyActive™ TFC membranes, featuring pure-gas CO₂ permeance of 1700–3100 GPU, representative of state-of-the-art CO₂/N₂ separation membranes. By designing and 3D-printing a counter-current permeation cell with optimized flow efficiency, we achieved a 33–41% increase in mixed-gas CO₂ permeance compared to traditional cells. Additionally, a comparison of sweep-gas and vacuum permeation methods revealed that vacuum operation mitigates downstream polarization, enhancing mixed-gas CO₂ permeance by 41%. These results underscore the critical role of permeation cell design and testing methods in accurately evaluating membrane performance, with significant implications for scaling up TFC membranes and optimizing industrial processes.

3D printing↗
DOE OSTI2025

Bridging the Gap Between Astronomical Datasets: From Proof-of-Concept to AI Model Deployment with Domain Adaptation

Artificial Intelligence is transforming astrophysics, from studying stars and galaxies to analyzing cosmic large-scale structures. However, a critical challenge arises when AI models trained on simulations or past observational data are applied to new observation— leading to domain shifts, reduced robustness, and increased uncertainty of model predictions. This talk will explore these issues, highlighting examples such as galaxy morphology classification and cosmological parameter inference, where AI struggles to adapt across different datasets. We will discuss domain adaptation as a strategy to improve model generalization and mitigate biases—essential for making AI-driven discoveries reliable. Notably, these challenges extend beyond astrophysics, affecting AI applications across physics and other scientific domains. Addressing them is essential for maximizing AI’s impact in advancing scientific research.

Ćiprijanović, Aleksandra [Fermilab]↗
DOE OSTI2025

Validation Gap Assessment of a MAP Package Containing Fresh, Metallic Sodium-Cooled Fuel

This report describes an assessment of sodium fast reactor assemblies loaded within an AREVA MAP package. The assessment was performed to determine the state of the validation basis for sodium fast reactor fuel within a transportation package originally intended for fresh, light-water reactor fuel assemblies. A similar study is being simultaneously released (Cumberland, 2025), and substantial parts of the explanatory text are identical to that parallel work, which follows the same workflow. Both studies employed the TSUNAMI-3D and TSUNAMI-IP sequences from the SCALE code system to determine correlation coefficients between various configurations and databases of validation assessments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Validation Gap Assessment of a TN B1 Package Containing Fresh, Metallic Sodium-Cooled Fuel

This report describes an assessment of sodium fast reactor assemblies loaded inside a Transnuclear B1 package. The assessment was performed to determine the state of the validation basis for sodium fast reactor fuel within a transportation package originally intended for fresh, light-water reactor fuel assemblies. The study employed the TSUNAMI-3D and TSUNAMI-IP sequences from the SCALE code system to determine correlation coefficients between various configurations and databases of validation assessments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Critical Knowledge Gaps for Coastal Systems: Research Priorities for Coastal Regions of the Southeastern United States

Coastal watersheds and shorelines are home to 52% of the U.S. population and provide trillions of dollars of economic and ecosystem services each year. However, these regions are subject to increasing frequency and intensity of compounding hazards that generate substantial damages. Sea level rise is increasing flooding and salinization of low-lying areas; periodic storm surges push ocean water farther inland and increase salinity in freshwater resources. Changing weather patterns, water management, and land cover all affect water and sediment flow to the coast in ways that exacerbate extreme flooding and drought. These impacts eventually drive systems past tipping points and lead to rapid and often irreversible transformation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Bridging the Gap between Cosmological Simulations with Graph Neural Networks and Domain Adaptation

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross dataset tasks (up to 28% better relative error and up to almost an order of magnitude better χ 2 ). Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

97 MATHEMATICS AND COMPUTING↗