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An integrated approach to assessing mobile crane mat requirements based on a novel approach to ground bearing pressure calculations and a redefining of crane mat selection and optimization

  • Author / Creator
    Ali, Ghulam M
  • Modular construction is adopted to increase construction efficiency and curtail waste. The fortitude of modular construction is high-capacity mobile cranes, of which hydraulic and crawler cranes are the most widely used. With the surge in weight of modules, the mobile crane's ground bearing pressure also escalated. The traditional primary status quo technique to avoid ground failure is to estimate the ground bearing pressure employing the fundamentals of statics, considering uniform ground bearing pressure under hydraulic crane mats and crawler crane tracks along the width of the track, which contradicts the finite element analysis results.
    Additionally, these cranes count on the stability of the ground for safe rigging and heavy lifting. The conventional approach uses timber crane mats under the crane tracks/outriggers. The crane rental industry's primary cost driver is crane mat crowding (2–3 layers of timber crane mats), directly linked with crane mat selection, on-site optimization, and crane mat design. Moreover, timber crane mats are not durable as they last for 2–3 years only and entail wood waste (crashed timber) as a by-product. The proposed research aims to reassess the crane mat requirement on-site by proposing a novel mobile crane ground bearing pressure calculation methodology to overcome the limitations of the traditional method. In contrast to the traditional approach, the present study proposes a new methodology to not only calculate the ground bearing pressure under mobile crane tracks/crane mats employing a combined loading approach but also to calculate the ground bearing pressure anywhere on the crawler crane track or hydraulic crane mat area, which can establish the ground bearing pressure profile in detail. In the form of a computer application, the proposed ground bearing pressure methodology for hydraulic cranes is linked with five crane mat selection criteria for the practitioners to select the suitable crane mat for the job.
    This thesis proposes an agent-based greedy algorithm and Reinforcement Learning approach for automated crane mat layout optimization as an innovative approach to developing sustainable crane mat layouts. This approach takes into account the site constraints and can be applied to mitigate crane mat crowding on construction sites. The crane mat optimization, using both methods, is applied to achieve the maximum area covered with the minimum number of crane mats used. The results demonstrate that the practitioner time spent preparing a crane mat layout plan/drawing can be reduced considerably, in some cases by minutes, with more uniform and cost-effective crane mat optimization outcomes.
    The allowable soil bearing capacity is another substantial factor affecting the selection and optimization of crane mats, exceeding the ground bearing pressure under the crane mat for safe operation. Existing allowable soil bearing capacity equations, which are based on shallow foundations, need to incorporate crawler and hydraulic crane ground footing area with variable loading. Typically, crane rental companies rely on the client to provide the allowable soil bearing capacity value based on which to estimate the requirements for remedial efforts to stabilize the ground. In this regard, crane mats and soil compaction can be applied to overcome poor soil bearing capacity and ensure a safe lift. The pragmatic approach adopted in this thesis is to develop an algorithm, formalized in a computer application, that can estimate the allowable soil bearing capacity (particularly in the context of crane work) based on a construction site's geotechnical reports and crane ground footing.

  • Subjects / Keywords
  • Graduation date
    Fall 2022
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/r3-89zt-c756
  • License
    This thesis is made available by the University of Alberta Library with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.