Accelerated Foundation Repair/Retrofits for Capacity Upgradation and Strengthening

Project Information

Link to Latest Report: Coming Soon


The economic case for foundation reuse in bridge replacement/renewal projects is compelling.Foundation reuse can lead to significant cost savings as in bridge replacement project the typical cost of substructure can be in the range of 40 to 50 percent of the total bridge cost. In the current practice, the foundation reuse approaches are developed as one-off application using an ad hoc approach requiring rediscovery of many selection and design aspects. Such efforts entail high engineering cost in both the design phase as well as in the implementation phase as multiple pathways have to be analyzed and proof-of-concept demonstrated for each use case. It is notable that in many cases of foundation retrofits, mini-/micropiles emerge as the preferred choice. However, the use of micropiles typically presents a challenge related to the variation in their performance from site-to-site and installation-to-installation. Indeed, for every implementation of micropiles in foundation retrofit project, 2-10% of the micropiles have to be proof tested or tested to failure. Therefore, a systematic study is needed that utilizes the experience of various case histories that exist in the literature to develop future research questions that can lead to standardization of foundation reuse by capacity upgradation and strengthening utilizing mini-


The proposed project objectives include:

  • The project will explore potential of data science and soil-structure interaction mechanics guided AI (machine learning) approaches to reuse of foundation. Further, the type of analyses and standardization envisaged goes well beyond the current practice in design (currently based upon FHWA methods whose database could be enhanced and which need major refinement for harmonizing ultimate and service limit capacity estimation), technology evaluation and implementation in construction.


The proposed project includes several tasks

  • Task 1: Literature Compilation.
    • Collection and collation of foundation reuse case studies based upon use of mini-/micropiles available in the literature or obtained through shareable data available with practitioners and DOTs. A thorough investigation of previous research and documented work in the analysis of axial and lateral capacity enhancement of existing foundation retrofitted with micropiles and related areas will be conducted. These case studies data will be assembled, analyzed, and critiqued to determine relevancy to this project.
  • Task 2: Evaluation of Case Studies
    • Critical evaluation of the case studies collected and collated in Task 1 will be performed to extract the data relevant to this project. The evaluation will consider all parameters related to 3 classes of micropile characteristics, namely, structural, geotechnical and construction. The parameters in these 3 classes will consist of: reinforcementtype, casing-type/length and grout material; the subsurface conditions, and construction technique.
    • Case studies will be categorized in terms of the completeness and of thoroughness of both quantitative data and descriptive information. Pertinent soil data will be obtained from soil data reports based upon in-situ investigations. In addition, the load testing data will consist both of the proof tests and the so-called “sacrificial” ultimate capacity field tests.
  • Task 3: Evaluation of Micropile Retrofit Design methods
    • All of the case studies documented in Task 2 will be evaluated against the predicted capacities based upon the widely recommended capacity estimation methods for both service and ultimate failure loadings. This evaluation will present the gap between the traditional design approaches recommended in the design manuals (and other similar documents) and actual capacities achieved in the field. Based upon the PI experience, the actual capacity achieved in the field by these foundation systems depend in a complex manner upon all the 3 classes of micropile characteristics identified in Task 2. Therefore, the capacities predicted by traditional method that do not account for a number of these characteristics cannot be systematically reliable.
    • The key purpose of the task will be to establish this gap in knowledge along with the descriptive identification of the sensitivity of micropile capacity to all of the characteristics. We will aim to develop a sensitivity ranking for these parameters, which will then feed into the AI and data science algorithms that will be explored in task 4.
  • Task 4: – Standardization of Foundation Reuse Specifications.
    • Develop research question that need further exploration in collaboration with external partners including FL DOT,contractors and practitioners, in particular how data science and soil-structure interaction mechanics guided AI (machine learning) approaches can be incorporated to increase the efficiencies in adopting micropiles for reuse of foundations. This step is expected to be particularly innovative and challenging since the parameter set for the design of micropiles is likely to consist of both quantitative and descriptive elements. Therefore, this last task will be of exploratory nature.

Research Team:
Principal Investigator:Anil Misra