The trade-off between computational efficiency and accuracy of various terramechanics simulation methods is a challenge that many engineers face when conducting analysis of off-road vehicle mobility. The Discrete Element Method (DEM) can capture complex phenomena within the soil, but requires substantial time and computing resources in comparison to the lower fidelity simple terramechanics methods such as the Bekker-Wong model. In this study, we propose a novel approach that seeks to strike a balance between efficiency and fidelity in simulating tire tractive capability in soft-soils. Our approach leverages DEM to determine Bekker-Wong parameters which encapsulate the bulk response of the DEM model and can predict accurate overall tractive performance. The process involves using DEM to generate soft-soil tire performance curves and using an optimization framework to determine simple terramechanics parameters, such as Bekker-Wong parameters, that best fit the DEM response. These parameters can then be used in other simulations for quantifying vehicle performance on soft-soil without the need for cumbersome DEM simulations. The results of the study demonstrate that the approach is promising with further refinement. Future work should focus on starting with more accurate DEM soil properties and scaling the method up to the full-vehicle level. If successful this work could ultimately provide a model with good predictive capability, while still allowing fast simulation times for agile design iteration and high run-count analyses.

This study seeks to improve upon existing methods of characterizing soft-soils for mobility simulations which use the Discrete Element Method. The study presents a novel approach for characterizing DEM properties based on Bevameter test data. The proposed method involves training a Reduced Order Model (ROM) to predict Bevameter results from DEM particle properties and using the ROM within a multi-objective optimization framework to determine the DEM properties which best fit a target Bevameter dataset. To demonstrate the efficacy of the approach, the trained ROM was used to generate DEM models meant to mimic the Bevameter response for a variety of field-tested soils. The accuracy of the resulting DEM models was evaluated using two validation methods. One in which the error in the resulting DEM properties is quantified, and one in which the error in the resulting DEM Bevameter response is quantified. The findings of this study provide compelling evidence that the proposed approach is a promising method for characterizing the properties of soil for DEM simulations using Bevameter data. The results indicate that certain enhancements are necessary for further refinement of the approach. However, once refined, this method is expected to offer a dependable and efficient means of soil model characterization.

This paper presents various simulation use cases together with a field example of how downhole physical measurements combined with a calibrated simulation running in a timely manner could have anticipated and potentially prevented the fishing of a drilling motor that twisted off. The timeliness of drilling decisions and how the characteristics of surface and downhole physical measurements affect simulation calibration and the influence of physical data on simulation fidelity are also discussed.

Drill string, drilling tool and drill bit failures are frequently incorrectly blamed upon the invisible geology through which they drill. Field engineers frequently report more severe downhole vibrations at rotation speeds other than those predicted by linear frequency-based finite element critical speeds analyses. The same multi-body dynamics simulation techniques used by the automotive and aerospace industries, however, are now being applied to capture the non-linear aspects of the drilling process and provide more realistic predictions of drilling performance. Simulation validation is achieved by comparing virtual data to physical data with an implicit understanding of the uncertainties of each. Recommendations are presented for improving the usefulness and the quality of physical drilling data which simulation can then also help assure. The ultimate objective is to deliver better quality boreholes which are less costly with fewer drilling tool failures. These novel simulation techniques are enabling manufacturers to benefit from lower development costs and shorter times to market with more reliable proprietary drilling tool designs. Drilling contractors are using simulations to optimize top-drive controls and drill more effectively. Product developers are able to configure higher performing and more optimal bottom hole assemblies. Operators are able to reduce overall drilling costs with the potential benefits of higher performing drilling automation systems and greater production from better quality boreholes.

Section 5510 of Fixing America’s Surface Transportation Act, 2015 (FAST Act) required the Secretary of Transportation to conduct a study on the effects of attaching a luggage compartment to the rear of a double-decker motorcoach, with respect to safety of vehicle operations, fire suppression capability, tire loads, and pavement impacts. This report presents the results of that study. The study was conducted through a combination of analysis and tests with a double-decker motorcoach. The three conditions were a reference loading condition, a regulatory loading condition, and a maximum loading condition. The reference or baseline condition had the load for passengers and luggage but no rear luggage compartment. The regulatory condition had a payload identical to the reference condition, but a rear luggage compartment was attached. In the maximum loading condition the motorcoach, with a rear luggage compartment attached, was loaded to its gross vehicle weight rating (GVWR). The rear luggage compartment did not affect safe maneuverability over the range of conditions tested. There is an unquantified concern that the compartment could contain heat in a severe engine compartment fire and lead to breaching the rear window. The tires and rims have adequate capacity for their loads. States must enact limits on tire and axle loads that are consistent with Federal Highway Administration (FHWA) regulations. The loads under all conditions may exceed some State limits with respect to the FHWA bridge formula.

Drivers of cargo tank trucks need special knowledge of vehicle and load dynamics, including slosh, to handle their vehicles safely. This knowledge is reflected by a tank vehicle (N) endorsement to the commercial driver’s license (CDL). Drivers of vehicles that carry intermediate bulk containers (IBCs) aggregating to 1,000 gallons capacity or more must hold an N endorsement, according to current regulations. The Federal Motor Carrier Safety Administration (FMCSA) requires technical information to help determine whether to modify this requirement. This research used simulations and experiments to identify the conditions and extent to which a commercial motor vehicle (CMV) with IBCs behaves differently from a conventional cargo tank truck of similar capacity and load. The simulations modeled the slosh of liquid loads in a single cargo tank and several combinations of IBCs. The slosh was simulated both by computational fluid dynamics (CFD) and by a simplified pendulum model that could be integrated with a commercially available model of a single-unit truck. Quantitative performance metrics showed that the effect of slosh in the IBCs was less than the effect of slosh in the 1,100-gallon tank in nearly all cases. Only in extreme cases were the slosh forces in the IBCs more than a few percent greater than the forces produced by an equivalent rigid, solid load. In the experimental portion of the research, professional tank drivers drove trucks carrying IBCs similar to those simulated. The drivers reported that, in the extreme maneuvers, they sensed the slosh slightly more than they would in a similar truck with dry freight.

The equations to generate a J-R curve from a four-point bend test on circumferentially cracked pipe have been known for many years. Given the experimental pipe load-displacement record and crack growth, the only impediment to routinely calculating pipe J-R curves is the requirement to know the non-cracked pipe elastic and plastic displacements. Traditionally, finite element analyses are used to find these displacements. This paper presents a semi-closed-form solution for the total (elastic plus plastic) non-cracked pipe displacements that eliminates the need to perform finite element analyses to calculate a pipe J-R curve.

Physical models are commonly used in the automotive industry. Accurate models exist for most automotive systems. However, few accurate models have been developed to model the individual components of automotive suspension dampers. Damper modeling is challenging due to the complexities associated with fluid flow and clearance nonlinearities, fluid-structure coupling, and overall sensitivity to parameter variations. This thesis focuses on the evaluation of gas bulk modulus, oil bulk modulus, Coulomb friction, effective mass of the body and valve resistance. The effect of these parameters on damper performance are analytically evaluated. The results show that the model is most sensitive to valve fluid resistance. Two experiments are presented. In the first experiment a simplified loading pattern was applied to the shims using steel forks. In the second experiment the displacement of the shims was measured while fluid was flowing through the valve. Although these experiments did not match exactly, valve shim stiffness calculated from each experiment led to accurate results when the model was run with these stiffness values. The overall model accuracy is adequate, though further work is needed to improve the modeling of shims and other components.