Exploratory Advanced Research Program Research Associates Program 2018 : [brochure]
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Summary
This document is a brochure summarizing the research conducted by associates in the Federal Highway Administration’s (FHWA) Exploratory Advanced Research (EAR) Program during 2018. The EAR Program, part of the National Research Council’s Research Associateship Program, facilitates short-term, high-risk research by postdoctoral and senior scientists to address critical issues in highway transportation. The brochure highlights specific projects across materials science, connected vehicle systems, human behavior, and performance assessment technologies. In materials science, researchers focused on advancing ultra-high performance concrete (UHPC) and asphalt mixtures. Rafic El-Helou developed material testing standards and design methodologies for UHPC to support resilient infrastructure, including prototyping pretensioned bridge girders. Luis Felipe Maya Duque validated direct tensile-test methods for UHPC to improve quality control and structural design codes. In asphalt research, David Mensching and Jong-Sub Lee developed performance-based design frameworks using index parameters and mechanistic models to predict fatigue and thermal cracking. Their work identified that voids in mineral aggregate and air void content significantly influence fatigue life, providing data for performance-related specifications. Additionally, Jessica Silva investigated inorganic curing compounds as durable alternatives to organic membranes, while Danial Esmaili analyzed large-scale tests of geosynthetic-reinforced soils to define service limit states for bridge abutments. Pavement management and structural assessment were addressed through modeling and non-destructive testing. Seyyedmahdi Nasimifar developed analytical models to correlate traffic speed deflection device measurements with pavement structural responses, enabling better prediction of deterioration and remaining structural life. Emmanuel Bolarinwa developed new vehicle-tire and contact friction models to assess safety performance, while other projects explored nano-additives for concrete and asphalt interfaces. The brochure also outlines research in connected highway systems and human behavior. Projects included cost-benefit analyses of connected and automated vehicles, development of eco-cooperative adaptive cruise control, and knowledge-based signal timing optimization. Human behavior studies examined the effectiveness of high-visibility crosswalks, operational analyses of alternative intersection designs, and the integration of driving simulation with naturalistic driving data to advance crash modeling. The significance of this research lies in its contribution to long-term improvements in transportation systems. By standardizing UHPC design, enhancing pavement management tools, and integrating advanced vehicle technologies, the EAR Program supports the development of more durable, efficient, and safe highway infrastructure. The findings provide a basis for updated design codes, performance specifications, and management strategies that optimize investment decisions and reduce lifecycle costs.
Key finding
The document compiles summaries of completed research projects from the 2018 Exploratory Advanced Research Program, detailing advancements in pavement materials, structural design, and traffic safety modeling.
Methodology
review
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (47 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 44 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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- Applied Guidance: countermeasure evaluation
- Empirical Findings: crash risk outcomes
- Methodological Resource: dataset resource