<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
    <atom:link href="https://rip.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
    <description></description>
    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
    </image>
    <item>
      <title>Instrumentation And Monitoring For G-Beam/Stillwater Avenue Bridge Replacement</title>
      <link>https://rip.trb.org/View/2582413</link>
      <description><![CDATA[In the proposed project, the research team plans to deploy an extensive instrumentation and communication system that will be embedded in the G-Beam girders proposed for the Stillwater Avenue bridge in Orono/Old Town.  Some of the details of the specific monitoring plan will need to be deferred to coincide with girder design.
The study will include the following. First, an array of fiber optic cabling will be installed along the longitudinal beam axis at different locations relative to the neutral axis.  Each cable will include discrete sensors at different locations along the beam axis to capture strain at those points.  Second, an array of accelerometers will be located it key locations in order to capture frequencies and modes of vibration during service.  Both the accelerometers and the fiber optic system will be connected to a communications network that both collects data from the sensor array and broadcasts the data over a wireless network to a server at University of Maine (UMaine).  Depending on collection rates, the data will either be transmitted over a conventional 5G cellular network, or more likely via a closed network that sends the data through a series of discrete repeaters in between the bridge site and the server.  Third, the team proposes a system of digital cameras that will be used both to trigger the acquisition and transmission system, but also through machine vision, be able to identify the vehicle type (e.g. number of axles.)  Once triggered, the array of strain gages and accelerometers, will preprocess data and send to the UMaine server.  In this way, resulting strain and vibration data can be tied to load types.  Fourth, a weather station will monitor current temperature, sunlight, and relative humidity data to complement the acquired structural data.  Depending on design issues, additional on-site sensors can monitor water level, ice status, and other environmental conditions that may be relevant. Finally, we will conduct diagnostic live load tests on the completed structure immediately before it is opened to traffic and approximately one year after its completion]]></description>
      <pubDate>Thu, 31 Jul 2025 14:23:33 GMT</pubDate>
      <guid>https://rip.trb.org/View/2582413</guid>
    </item>
    <item>
      <title>Large-scale Testing for Detecting Changes in Track Modulus with Low-cost Sensors Installed on Rolling Stock



</title>
      <link>https://rip.trb.org/View/2572334</link>
      <description><![CDATA[U.S. railroads transport 1.6 billion tons of freight over more than 140,000 miles of track each year. Safe and efficient operation of such a vast infrastructure requires extensive monitoring, evaluation, and maintenance of its track systems. Track modulus is a critical parameter in the design, analysis, and maintenance of railroad track, as it is indication of  the material stiffness below the rail comprising the combined stiffnesses per unit length of rail, plates, ties, ballast, and subgrade. Locations of “soft” track can cause increases in rail deflections and stresses, which increases the rate of rail deterioration. Traditionally, track modulus is measured onsite using static deflection testing where a known load is applied to the track, the resulting deflection is measured, and this deflection is extrapolated to the track modulus. However, this is time consuming and labor-intensive, especially if measurements are to be taken at multiple points along the track. To address the challenges with track modulus measurement, this research attempts to refine existing methods and expand the scale of monitoring by leveraging data from railcars to identify problem locations on the track and relate measured responses to specific track deficiencies. The approach allows making continuous estimations over long sections of the track and also is less costly, as self-contained acceleration and data acquisition systems are inexpensive and easy to attach to the vehicle bodies. This research will use technologies such as the ground penetrating radar (GPR) and track geometry cars in combination with low-cost sensors placed on the existing plant of rolling stock for accelerated track monitoring. Track response to track conditions will be measured. Constitutive load-deflection relationships will be established between track condition, loading, and deflection to determine the track modulus. The modulus will be characterized by leveraging the mechanics that relates vehicle accelerations to the condition of track upon which the instrumented vehicle travels. The research team is experienced in the use of low-cost accelerometers for bridge monitoring and assessment, where it established the mechanistic relationships between loading and response under various conditions and showed the feasibility of determining quantifiable, specific conditions from the acceleration data. Using this expertise and experience, the team now seeks to develop mechanics-based relationships that correlate railcar body acceleration profiles to track behavior and, eventually, track condition. This project is the next step towards full implementation, where it will use previously characterized conditions on a model test to support the constitutive load-deflection relationships. The overall impact of this work will be the widespread monitoring of track infrastructure through the installation of low-cost accelerometers on existing rollingstock. The industrial partner, BNSF, will provide support and help with implementation.]]></description>
      <pubDate>Wed, 09 Jul 2025 16:08:22 GMT</pubDate>
      <guid>https://rip.trb.org/View/2572334</guid>
    </item>
    <item>
      <title>Experimental and Analytical Modeling of Tunnels in Squeezing Ground Conditions (UTI-UTC 14)</title>
      <link>https://rip.trb.org/View/1500818</link>
      <description><![CDATA[Ground squeezing resulting in large plastic zone and large convergence is one of the most challenging problems in tunneling. 
The squeezing problem in tunnels is often associated with high overburden, low compressive strength of geomaterial, tunnel excavation sequence, competency ratio, tangential strains or the mineralogy of the rock or soil. One or more factor(s) have been used in the literature to define problem of squeezing. Various empirical, semi-empirical and analytical correlations have been developed over the years, but many correlations are problem specific and contradicts with each other. In this work, an experiment will be designed that will study the squeezing problem in tunnel under soft ground conditions. The experimental will be performed on a cubical specimen of a soft rock/soil/synthetic material with a size of 30x30x30 cm³. The specimen will be subjected to compressive poly-axial stress state in all three directions, i.e. σ1>σ2>σ3. A small model earth pressure balance (EPB) tunnel boring machine (TBM) will be designed that can simulate excavation similar to real on site tunneling. Monitoring will be done using acoustic emission (AE), borehole extensometer, strain gages and accelerometers will be installed in TBM and on the cubical specimen. The critical conclusions and correlation developed from the experimental results will contribute significantly and will be give better insight into the problem of tunnel squeezing.]]></description>
      <pubDate>Fri, 16 Feb 2018 19:26:13 GMT</pubDate>
      <guid>https://rip.trb.org/View/1500818</guid>
    </item>
    <item>
      <title>Incorporating Mobile Technology into the GPS/Web-GIS Method for Travel Survey and Research</title>
      <link>https://rip.trb.org/View/1236083</link>
      <description><![CDATA[Traditional paper and phone travel surveys are expensive, time consuming, and have problems of missing trips, illogical trip sequences, and imprecise travel time. Global positioning system (GPS) based travel surveys can avoid many of these problems and are becoming increasingly popular in major cities worldwide. However, there is GPS signal loss or degradation in high-density cities such as New York City (NYC) where urban canyon effects are significant, underground subway and commuter rail travels are extensive, GPS cold/warm start problems are obvious, and mixed land use is common. This project proposes to develop application software of using smartphones to combine GPS/GIS/Internet/mobile technologies for travel survey and research. It will put together the geographic information system (GIS) algorithms and Web GIS developed in the past few years to produce efficient results for the University Transportation Research Center (UTRC) funding. Using smartphones has many advantages over using handheld GPS loggers in collecting travel survey data. In addition to satellite signals, smartphones can use WiFi and assisted GPS provided by cell phone carriers to log locations. Smartphones with Internet connections allow survey respondents to interact real time with the GIS server to verify results from the GIS algorithms, answer questions about trip purposes, and provide photos of activity stops if necessary. Smartphones are typically equipped with accelerometers that can output acceleration measurements to help mode detection underground. Logistically, since smartphones are becoming very popular, using smartphones can eliminate costs associated with purchasing, distributing, and collecting GPS loggers. The application software developed from this project will be useful for future travel surveys in this region and to provide accurate data for updating the New York Best Practice Model. The research approach can be applied elsewhere as well. The two principal investigators (PIs) in this project are mid-career and junior faculty members in the UTRC consortium. They adopted this multi-disciplinary and multi-college approach to tackle a problem in applying innovative GPS/GIS/Internet/mobile technologies to meet the needs of travel demand forecasting and transportation planning. The graduate students hired for this project will particularly benefit from this unique approach and have the chance to gain skills and experience of using new technologies. The results from this project will also be used by the PIs in the education of students in transportation and GIS research at both Hunter College and City College.]]></description>
      <pubDate>Thu, 03 Jan 2013 15:40:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/1236083</guid>
    </item>
  </channel>
</rss>