SEARCH · Engineering Papers
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.
A guiding principle for conducting research in technology, science, and engineering, leading to innovation is based on our use of research methodology (both qualitative and qualitative). A brief review of research methodology will be presented with an overview of NASA process in developing aeronautics technologies and other things to consider in research including what is innovation.
A guiding principle for conducting research in technology, science, and engineering, leading to innovation is based on our use of research methodology (both qualitative and quantitative). A brief review of research methodology will be presented with an overview of NASA process in developing aeronautics technologies and other things to consider in research including what is innovation.
Presentation to cover how to use and understand the NEQAIR code. The avenues to obtain the code will also be discussed.
The purpose of this document is to introduce a new user to the procedures for overset CFD analysis by building scripts based on the CGT Script Library. Parameterized inputs are built into the steps of the process which include creation and manipulation of geometry, and surface and volume meshing. In preparation for performing computations in the flow solver, further steps are constructed for specification of inputs for domain connectivity, flow solver boundary conditions, and components for computation of aerodynamic forces/moments. The JCLV rocket will be used as an example geometry for this demonstration.
Presentation to cover how to use and understand the NEQAIR code. The avenues to obtain the code will also be discussed.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
NREL’s REopt Lite web tool helps users evaluate the economic viability of distributed photovoltaic (PV), wind, battery storage, combined heat and power, and thermal energy storage systems. REopt Lite was designed for locations within the United States; however, with appropriate adjustments, it is possible to use most of its features for international locations.
This workshop will provide a comprehensive overview to Windfarm Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT), NREL's first wind O&M software model. The session will discuss how to utilize WOMBAT to answer O&M research questions covering land-based, offshore, and distributed wind farms. It will offer an introduction to the model and how it operates. The team will then offer a demonstration of the various modeling parameters by converting the CORE Wind Floating Wind Strategies O&M Assessment assumptions into an analysis-ready configuration, diving into the results, and exploring further model variations.
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.
Not Available
Not Available
Not Available
Deep learning (DL) has been used to design deep neural networks (DNNs) which have recently been applied to solving inverse problems in artificial electromagnetic materials (AEMs). Although inverse problems are often ill-posed, and therefore are difficult to solve, deep inverse models (DIMs) have achieved impressive results often surpassing capabilities possible with other approaches. We overview the process of deep inverse learning applied to AEM problems, including the building of data sets, design of a forward model, and comparison of inverse approaches including limitations. We conclude by detailing some important outstanding issues of deep inverse design of AEMs, and present an outlook of this exciting field.
Radio frequency (RF) sheaths occur under a wide variety of conditions when RF waves, material surfaces and plasma coexist. RF sheaths are of special importance in describing the interaction of ion cyclotron range of frequency (ICRF) waves with the boundary plasma in tokamaks, stellarators and other magnetic confinement devices. In this article the basic physics of RF sheaths is discussed in the context of magnetic fusion research. Techniques for modelling RF sheaths, their interaction with RF wave fields and the resulting consequences are highlighted. The article is intended as a guide for the early-career ICRF researcher, but it may equally well serve to provide an overview of basic RF sheath concepts and modelling directions for any interested fusion scientist.