Engineering Papers⌕ Search
Home/Archive/DOE OSTI

DOE OSTI · 1771484

Containment seal

Noel, Derek
View original source ↗Read source document ↗Export metadata ↓

Abstract

A containment seal seals a cable or tube to an opening accessing a containment vessel. The containment seal includes a lower body that attaches over the opening into the containment vessel. The cable or tube is inserted through a hole that extends axially through an upper body of the containment seal. Compression fittings are attached to the top and bottom ends of the upper body sealing the cable inside of the upper body. The cable sealed inside of the upper body in inserted through the lower body and into the opening accessing the containment vessel and a lower portion of the upper body is seated into the opening formed in the lower body. A retaining device compresses the upper body down against the lower body forming a seal between the upper body and lower body.

Explore related subjects

42 ENGINEERING

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Noel, Derek. 2020-10-06. Containment seal. https://www.osti.gov/biblio/1771484

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

KEEP EXPLORING

Related reports

DOE OSTI2026

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↗