Volpe National Transportation Systems Center

Ballast serves a critical role in railway track stability by supporting rails and crossties, distributing loads, and facilitating drainage. However, its structural integrity can be compromised due to fouling and moisture infiltration, leading to reduced shear strength and stiffness. While geogrid stabilization has been widely recognized for improving ballast performance, its effectiveness under different moisture conditions remains less understood. The objective of this study is to evaluate the effect of moisture content and geogrid stabilization on the dynamic characteristics of fouled railway ballast using Bender Element (BE) sensor technology. Laboratory box tests were performed on ballast specimens with a fouling index (FI) of 25.3, incorporating gravimetric moisture contents ranging from 0% to 12% by weight of fines smaller than 9.5 mm (3/8 in.). Shear wave velocities (Vs) were measured using BE sensors embedded within the ballast layer to estimate small-strain shear modulus (Gmax) characteristics. Geogrid-stabilized specimens were compared to non-stabilized control cases under both dry and wet states. The test results showed that (Vs) and (Gmax) increased for up to 6% moisture and then decreased at higher moisture levels, indicating a transition from stabilizing to lubricating effects of added moisture on the ballast fines. Under both dry and wet conditions, geogrid-stabilized ballast samples exhibited higher shear wave velocities and stiffness values than the control. These findings demonstrate the value of field-installed BE sensors for evaluating ballast layer stiffness and monitoring the performance improvement provided by geogrid stabilization of track substructure under varying moisture conditions.

As quantum computing advances, the cryptographic algorithms that underpin confidentiality, integrity, and authentication in Intelligent Transportation Systems (ITS) face increasing vulnerability to quantum-enabled attacks. To address these risks, governments and industry stakeholders are turning toward post-quantum cryptography (PQC), a class of algorithms designed to resist adversaries equipped with quantum computing capabilities. However, existing studies provide limited insight into the implementation-focused aspects of PQC in the ITS domain. This review addresses that gap by evaluating the readiness of vehicular communication and security standards for adopting PQC. It examines in-vehicle networks and vehicle-to-everything (V2X) interfaces, and investigates vulnerabilities at the physical implementation layer of cryptographic hardware and embedded platforms, primarily exposure to side-channel and fault injection attacks. The review identifies thirteen research gaps: non-PQC-ready standards; constraints in embedded implementation and hybrid cryptography; interoperability and certificatemanagement barriers; a lack of real-world PQC deployment data in ITS; and physical-attack vulnerabilities in PQC-enabled vehicular communication. We present several future research directions, including updating vehicular communication and security standards, optimizing PQC for low-power devices, enhancing interoperability and certificate-management frameworks for PQC integration, conducting real-world evaluations of PQC-enabled communication and control functions across ITS deployments, and strengthening defenses against AI-assisted physical attacks. A phased roadmap is presented that aligns PQC deployment with regulatory, performance, and safety requirements, thereby guiding the secure evolution of ITS in the quantum computing era.

The Action Plan for Rail Energy and Emissions Innovation proposes actions to reduce and nearly eliminate emissions in the U.S. rail sector, in line with the U.S. economy-wide goal of net-zero greenhouse gas (GHG) emissions by 2050. It also proposes actions to leverage the rail system to reduce emissions from other modes. The national goal of achieving a zero-emission freight system by 2050 draws our attention to the fact that freight transport cannot be addressed simply mode by mode, but it should instead be treated as an interdependent system. This is especially true when pursuing decarbonization. This action plan presents how both rail transport and decarbonization intersect with our national transportation decarbonization blueprint, the decarbonization of the freight system, and national transmission goals. The intended audience of this report is the stakeholders who will advance rail decarbonization in a just and economical way by propelling the suite of actions listed here. This includes government at all levels, rail companies, locomotive manufacturers, labor unions, Amtrak, and more.

<p>Previous research examining locomotive train horns has suggested that certain characteristics, such as the number of flutes used and the frequency components of flutes, may enhance the effectiveness of the horn as a warning device. The current research sought to examine these findings by using recordings of standard train horns that varied in their sound characteristics. A signal detection procedure was used in which participants were asked to resp ond when they noticed a locomotive horn played through a background of in -car noise. Participants were also simultaneously engaged in a visual tracking task in order to impose additional attentional demands similar to those encountered by a motorist. Results of the study are largely consistent with previous tests of locomotive train horn efficacy; however, the effects of isolated characteristics in real horns appear to be interactive rather than additive. Additional findings also suggest that detection may also be dependent on whether the demands of driving and distractions leave sufficient attention left to detect and react to the train horn. Results are discussed in terms of implications for motorist safety and design of locomotive horns.</p>

BACKGROUND AND AIM: Ambient ultrafine particles (UFP; 0.1 micrometers aerodynamic diameter), primarily from vehicle combustion in urban areas in the US, have no ambient air quality standards. In large part, this is because there is no evidence from large, prospective studies of mortality. METHOD: We utilized a published high-resolution (hourly, 20-m-by-20-m), predictive model of particle number concentration (PNC, a surrogate for UFP) for the cities of Boston and Chelsea, Massachusetts, in the northeastern US. The U.S. EPA’s latest meteorological preprocessors were used to generate model input data for temperature, wind speed and direction, atmospheric stability, and other necessary variables. The PNC model was then adjusted for residential and occupational time-activity using surveyed data, retrospectively for people enrolled in the Boston Puerto Rican Health Study (BPRHS). Mortality in this cohort has been high (295 deaths out of 1500 participants). RESULTS: The PNC model estimated exposure for all participants in the BPHRS cohort within the two study areas for every hour from 2004 to 2021. Median modeled ambient hourly PNC decreased over time in both Boston and Chelsea (13,000 and 16,000 particles/cm3 in 2004 versus 4600 and 4700 particles/cm3 in 2021, respectively). Previous studies in the BPRHS of cardiovascular measures and CAFEH study found associations with increased PNC and time-activity adjusted PNC. Adjustment of exposure for time activity and tests of association with mortality are in progress and will be reported at the conference. CONCLUSIONS: This analysis, although of a small prospective cohort, has the potential to provide early evidence for or against association of traffic UFP with mortality due to the high mortality rate, contributing to filling a critical need in the air pollution policy arena.