Search NASA⌕ Search

DOE OSTI · 1433374

Article and method for making an article

Abstract

An article and a method for making shaped cooling holes in an article are provided. The method includes the steps of depositing a metal alloy powder to form an initial layer including at least one aperture, melting the metal alloy powder with a focused energy source to transform the powder layer to a sheet of metal alloy, sequentially depositing an additional layer of the metal alloy powder to form a layer including at least one aperture corresponding to the at least one aperture in the initial layer, melting the additional layer of the metal alloy powder with the focused energy source to increase the sheet thickness, and repeating the steps of sequentially depositing and melting the additional layers of metal alloy powder until a structure including at least one aperture having a predetermined profile is obtained. The structure is attached to a substrate to make the article.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lacy, Benjamin Paul, Schick, David Edward, Kottilingam, Srikanth Chandrudu. 2018-04-03. Article and method for making an article. https://www.osti.gov/biblio/1433374

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Large language models for transportation research: Methodologies, state of the art, and future opportunities

The rapid rise of large language models (LLMs) is transforming transportation research, with significant advancements emerging between 2023 and 2025, a period marked by the inception and swift growth of adopting and adapting LLMs for various transportation applications. Despite these significant advancements, however, a systematic review and synthesis of the existing literature remains lacking. This paper aims to fill this gap by providing a comprehensive review of the methodologies and applications of LLMs in transportation. We explore key applications, including autonomous driving, travel behavior prediction, and general transportation-related queries, alongside LLM methodologies such as zero- or few-shot learning, prompt engineering, and fine-tuning. From the review, critical research gaps are identified. From the methodological perspective, many of the research limitations can be addressed by integrating LLMs with existing tools and refining LLM architectures. From the application perspective, research opportunities for LLMs to address various transportation challenges are also explored. By synthesizing these findings, this review not only presents the state-of-the-art LLM adoption and adaptation in transportation, but also proposes future research directions as well as insights and recommendations for policymakers and practitioners, paving the way for greater LLM-driven research innovations in transportation in the future.

42 ENGINEERING↗