Engineering Papers⌕ Search

DOE OSTI · 1863849

ENG 572 Interim Report

Abstract

Sandia National Laboratories is a Federally Funded Research and Development Center (FFRDC) founded in 1949 with the mission of developing and testing the non-nuclear components of nuclear weapons. Sandia has since been involved with numerous projects to support the Department of Defense’s (DOE) National Nuclear Security Administration (NNSA). One such set of projects has been implementing over-the-road transportation security enhancements. Under this program, Sandia National Laboratories (SNL) has worked to develop interface compatibility modifications for existing shipping configurations. This summer I will be working with a line of trailers that have been used to transport high asset cargo. These vehicles have successfully traveled millions of miles without any accidents over the course of 15 years. The primary motivation for the work that I will complete this summer is to provide support for existing electronic communication technologies implemented at SNL. As part of an ongoing project to implement modifications to a trailer system, I will focus primarily on the characterization and testing of thermal electric coolers (TEC). Within the scope of the trailer project, these devices provide temperature control for lasers used on optical communication boards (OCB).

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zhao, Jeffrey. 2020-06-19. ENG 572 Interim Report. https://doi.org/10.2172/1863849

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↗