Technical Symposia Abstracts

  Each technical talk will last 20 minutes, with a 15 minute presentation followed by 5 minutes of questions and answers. We will start and end on time so that the parallel sessions are synchronized. The session lead may open the session with brief remarks about the theme. Presentations will start promptly, managed by the session lead.

Technical Session 1A – Autonomy
Session Leads: Dr. Paramsothy Jayakumar, Dr. Matt Castanier

1A1: Improving Energy Efficiency and Mobility of Off-Road Connected Fleets via Route Preview and Cooperative Control
Quad members: Ardalan Vahidi (PI), Shahab Karimi, Angshuman Goswami, Alireza Fayazi (Clemson University); Chen Zhang (Ford Motor Corp); Paramsothy Jayakumar (U.S. Army TARDEC)

        Improvements in fleet energy efficiency and safety are of paramount importance to the Army. A novel path-planning algorithm as part of a decision support tool for off-road scenarios was developed last year based on low-order vehicle models. To capture interactions with off-road terrain with higher fidelity, a three-dimensional 14 degree of freedom model for off-road vehicle dynamics is developed and tested while traversing a pre-designed off-road surface. The model will be used to define vehicle dynamic constraints for the path planning algorithm.
        On the experimental front, a scaled vehicle-in-the-loop testbed is built in which a scaled autonomous vehicle communicates and collaborates with other (simulated) vehicles. Exchange of information between the real and simulated vehicles via a backend computational server complements existing soil and terrain maps to improve fleet mobility.

1A2: Enhanced Multi-Robot Reconnaissance Through Terrain-Based Energy Prediction
Quad members: Kira Barton (PI), Lauro Ojeda (Co-PI), Michael Quann (Presenter) (University of Michigan); William Smith, Denise Rizzo, (U.S. Army TARDEC); Frank Koss, Andrew Dallas (Soar Technology, Inc.)

        Autonomous robots have significant potential for reconnaissance and environmental monitoring applications. Ground robots, in particular, are performing reconnaissance missions in places that are too hazardous for humans. However, these robots are constrained by energy limitations that are impacted by uncertain environments and harsh terrains. The purpose of this work is to develop methods for improving the efficiency of reconnaissance missions through energy awareness. To address such limitations, robot energy usage is spatially modeled with a Gaussian Process (GP) through measurements collected during the mission. The resulting energy predictions are incorporated into a centralized waypoint-based strategy with the goal of minimizing the uncertainty of a spatial-temporal field, subject to ensuring the robots' return to recharging locations. We present simulation and experimental results for a multi-robot system to demonstrate the effectiveness of incorporating energy predictions into reconnaissance missions.

1A3: SQUAD: Situational Awareness and Sustained Survivability through Man/Unmanned Teaming
Quad members: Dimitra Panagou (PI), William Bentz, James Usevitch, Mitchell Coon (University of Michigan); Thomas Meitzler, Neil Cooper, Bob Severinghaus (U.S. Army TARDEC); Andrew Dallas (SoarTech)

        The SQUAD project is motivated by the need for protection of Ground Vehicle systems against Aerial Threats, and in particular, against small Unmanned Aerial Vehicles (UAVs). It is thus of vital importance that GVs are equipped with systems that can detect and act against small UAVs. The project aims thus at developing proactive and reactive countermeasures against aerial threats. In this talk we will review our recent algorithmic developments and experiments towards an aerial sensing/surveillance system of UAS that relies on our notion of dynamic coverage control, our initial algorithmic developments on resilient communication topologies in swarms of UAS, as well as our algorithmic developments on multi-player (UAS) target-attacker-defender games.

1A4: Flexible Multibody Dynamics Approach for Tire Dynamics Simulation
Quad members: Hiroyuki Sugiyama (PI), Hiroki Yamashita (The University of Iowa); Paramsothy Jayakumar (U.S. Army TARDEC); Ryoji Hanada (Yokohama Rubber); SeeChew Soon (Caterpillar Inc.)

        A high-fidelity physics-based deformable tire-soil interaction model that can be fully integrated into a monolithic multibody dynamics solver is developed for off-road mobility simulations and validated against test data. A locking-free nine-node brick element is proposed for modeling deformable terrains using the multiplicative finite strain plasticity theory along with the capped Drucker-Prager failure criterion. The soil model is validated against the triaxial soil compression test data. The moving soil patch technique is applied such that the soil behavior only in the vicinity of the rolling tire is solved to reduce the model dimensionality. Finally, the proposed off-road tire-soil interaction simulation capability is validated against test data obtained from an indoor soil bin mobility test facility, including the effect of wheel loads and tire inflation pressures on the tire forces and rolling resistances.

 

Technical Session 1B – Fuels & Engines
Session Leads: Dr. Peter Schihl, Mr. Eric Gingrich

1B1: Bulk Modulus of Compressibility Measurements of Conventional and Alternative Military Fuels
Quad members: Taemin Kim, Andre Boehman (PI) (University of Michigan); Eric Sattler (U.S. Army TARDEC); Peter Attema (Detroit Diesel/Daimler)

        This project concerns the bulk modulus of conventional and alternative jet fuels, and jet fuel surrogates and investigation of the impact of bulk modulus of fuel on fuel injection timing in pump-line-nozzle type fuel supply systems. A single cylinder, direct-inject, pump-line-nozzle type fuel supply engine is being configured for the purpose of the investigation of the different injection timing shifts with these alternative and conventional jet fuels. During the past year, the engine has been installed in a test cell, instrumented for combustion and fuel system dynamics analysis. Testing is ongoing. The outcome will be a correlation of the relationship between the isothermal bulk modulus and the injection timing shift, which can help guide the calibration and design of fuel injection systems.

1B2: Simulations for JP-8 Mechanism Optimization and Validation
Quad members: Jason Martz (PI), Jordan Lee, Shuqi Cheng (University of Michigan); Peter Schihl (U.S. Army TARDEC), Tim Edwards (AFRL); Jim Anderson (Ford)

        Detailed chemical kinetic mechanisms are needed for CFD simulations used to design Diesel engine combustion systems. Despite tremendous progress, state of the art Jet-A and JP-8 mechanisms remain inaccurate within the low temperature heat release (LTHR) and negative temperature coefficient (NTC) ignition regimes relevant to Diesel ignition. This project is focused on improving these mechanisms, in particular within the Diesel relevant ignition regimes. To this end, sensitivity analysis and optimization are used to identify and then modify relevant mechanism reaction rate parameters in order to reduce ignition delay errors. Combined with the atomistic computational project of Violi focused on mechanism reaction pathway development and the motored engine ignition studies of Boehman et al., our efforts will lead to more accurate Jet-A and JP-8 chemical kinetic models needed for the development of future Army engines.

1B3: Combustion Chemistry of Jet Fuels: Identifying New Reaction Pathways for Mechanism Development
Quad members: Angela Violi (PI), Paolo Elvati (University of Michigan); Peter Schihl (U.S. Army TARDEC); Tim Edwards, (AFRL); James Anderson (Ford)

        In recent years, there has been an increasing effort to incorporate complex reaction mechanisms in simulation of reacting flows. Indeed, computational fluid dynamic calculations of reactive flows have become an important part of the design of combustion devices, such as engines. One of the key components is the accurate description of the network of reactions that can happen during combustion. Current models are developed and optimized for specific conditions, and have little chance of producing reliable extrapolations to other conditions. There are two main major problems related to the development of predictive reaction models: accuracy of rate constants and ability to obtain a complete detailed mechanism. The former is usually addressed using high-level ab initio simulations to compute reaction rates; the latter represents a big challenge and almost no literature is available on this topic. In our project, we aim at addressing this challenge and developing a novel computational procedure to identify missing reaction pathways as well as main reaction pathways for the combustion chemistry of JP-8, using atomistic simulations.

1B4: Thermal Barrier Coatings for Reduction of Cooling Loads in Military Vehicles
Quad members: David Gatti (WSU), Marcis Jansons (PI), David Gatti (Wayne State University); Eric Gingrich (U.S. Army TARDEC); Shawn Dolan (Henkel of America, Inc.)

        Reductions in cooling loads are sought to reduce the considerable under-armor volume devoted to thermal management systems comprising ballistic grilles, fans, ductwork and radiators. Thermal barrier coatings (TBC) have military applications as a means of re-distributing energy from the cooling load to engine exhaust. Titanium-based coatings applied with a novel aqueous electro-deposition process show promise in overcoming the durability issues characteristic of previously researched materials. This presentation will discuss a simulation and experiment-based project that evaluates desirable TBC properties, the durability and thermal shock response of TiO2-based and other potential TBCs, and examines their thermal properties and in-cylinder behavior using optical diagnostic techniques.

 

Technical Session 2A – Electrification, Thermal Management
Session Leads: Mr. Aric Haynes, Mr. Scott Shurin

2A1: Optimal Warm-up of Lithium-Ion Battery from Sub-ZeroTemperatures
Quad members: Anna Stefanopoulou (PI), Jason Siegel, Shankar Mohan (University of Michigan); Yi Ding (U.S. Army TARDEC); Dyche Anderson (Ford)

        Operation at low temperature degrades battery performance, reducing available power and usable energy. To address these issues, we posed and solved two energy-optimal warm-up strategies in addition to developing decision tools on whether warm-up is feasible if the battery energy state falls too low. The first warm-up scenario involves a receding horizon optimal control problem for the bi-directional pulses that charge and discharge the cell at relatively high frequencies via an external capacitor. The results also define the capacitor size, time, and lost energy. The second control policy computes the optimal power discharge for self-heating the cell while minimizing the loss in state of charge. The methods are demonstrated via simulations and experiments on two Li-ion chemistries with high power capability typically used for conventional internal combustion engine starter (12V) or micro-hybrid in start-stop (48V) vehicle applications.

2A2: Robotic Range Extender: Power and Energy Management for a Quantized Hybrid Powertrain
Quad members: : Jason Siegel (PI), Anna Stefanopoulou (co-PI), Yuanzhan Wang, Miriam Figueroa (University of Michigan); Serhat Yesilyurt (Sabanci University); John (Jack) Hartner, Denise Rizzo (U.S. Army TARDEC); Tom Westrich (Ultra AMI Fuel Cells); Buz McCain (Ballard Power Systems Inc)

        This project addresses the need for quiet, long-life power sources for robotic vehicles which cannot be met by batteries alone (due to range), or with combustion engines (due to noise). A hybrid power source that combines a battery (BB2590) with small (245 Watt), propane-fueled solid oxide fuel cell (SOFC) is considered. A system model that takes into account degradation, which is particularly important and challenging for these systems due to the thermal stresses from the start-stop operation, was developed using physics based modeling techniques. The models are used to evaluate the impact of battery sizing and power split strategy on fuel efficiency, SOFC stack life, and battery cell life over realistic synthetic cycles. These cycles were developed using statistical models of the power measured from an instrumented PackBot, provided by TARDEC engineers.

2A3: A Thermal Bus with Passive and Active Cooling Strategies for Vehicle Thermal Management
Quad members: John Wagner (PI), Richard Miller (co-PI), Shervin Shoai Naini, Junkui (Allen) Huang (Clemson University); Denise Rizzo, Katie Sebeck, Scott Shurin (U.S. Army TARDEC); Arun Muley, David Blanding (Boeing Research and Technology)

        Thermal management solutions for military vehicles remain a challenge due to the variety of heat loads, payloads, propulsion system configurations and operation cycles. Cooling systems should meet the heat rejection requirements while minimizing the power consumption under adverse conditions. This study examines the integration of passive and active heat rejection strategies in a hybrid thermal bus architecture (e.g. heat pipes, composites, high conductivity materials, etc.) in parallel with traditional fluid designs. In an initial case study, pulsating and capillary heat pipes have been integrated as passive heat rejection pathways in the thermal bus. Mathematical models establish a basis for the numerical evaluation of the thermal performance during a convey escort driving profile. An experimental test bench is being designed to validate the computational results.

2A4: Computationally-Efficient Heat Convection Model for Electric Machines
Quad members: Heath Hofmann (PI), Yuanying Wang (University of Michigan); Denise Rizzo, Scott Shurin (U.S. Army TARDEC); John Wagner, Richard Miller (Clemson University); Ma Lin (Virginia Tech); Xiao Hu (Ansys Inc); Arun Muley (Boeing)

        Knowledge of the internal temperatures of electric machines is very important since the performance of these machines, such as their torque capability and efficiency, are greatly affected by these temperatures. In our previous work an FEA-based, computationally-efficient model of thermal conduction in the electric machine components was developed. In this project, a complementary computationally-efficient model of heat convection in the air regions of an electric machine is proposed. The model is based upon the exploitation of certain properties of the heat transfer equations (i.e., conservation of mass, momentum, and energy), which we have discovered exist under certain conditions as seen in electric machines. This in turn leads to the formulation of a system identification technique, the end result being a computationally-efficient heat convection model with very high accuracy.

 

Technical Session 2B – Structures, Reliability, Safety
Session Leads: Dr. David Lamb, Dr. Ravi Thyagarajan, Mr. Victor Paul

2B1: Confidence-based Reliability Assessment Accounting for Both Parameter Uncertainty and Model Bias for Insufficient Input and Output Experimental Data
Quad members: K.K. Choi (PI), Min-Yeong Moon, Hyunkyoo Cho (University of Michigan); David Lamb, David Gorsich (U.S. Army TARDEC); Nicholas Gaul (RAMDO Solutions, LLC)

        Conventional reliability analysis methods have been developed given (1) accurate input distribution models (i.e., no input distribution model uncertainty) and (2) accurate simulation model (i.e., no simulation model bias). However, in practical applications, insufficient input data are available and only limited output physical testing can be provided. As a result, there exist both uncertainties caused by limited input and output data. To handle both uncertainties, we propose a confidence-based reliability assessment that accounts for both uncertainty in input distributions model and simulation model. Both uncertainties are combined using hierarchical Bayesian model to obtain uncertainty distribution of the reliability. At user-specified target confidence level, confidence-based reliability and target output distribution are selected. After that, the validated simulation model is obtained using confidence-based bias correction.

2B2: Modeling of Materials for the Design of Lightweight and Resilient Vehicle Structures
Quad members: Nick Vlahopoulos (PI), Alyssa Bennett (presenter) (University of Michigan); Ravi Thyagarajan, Matthew Castanier (U.S. Army TARDEC); Nam Purush (BAE Systems)

        This project pursues the development of modeling strategies for materials that can contribute to the blast mitigation of structures. Implementing shear thickening fluids (STFs) in plate armor may provide a new means of shock absorption mechanism in ground vehicles; the viscosity of STFs increases significantly at high shearing rates. The work which will be presented focuses on determining whether the behavior of STFs can be utilized for blast mitigation in ground vehicles by studying the effects of Coulomb damping in a multilayer plate. A multi-layer plate model was constructed in LS-DYNA with Coulomb damping between layers and then was subjected to blast loads generated by the Friedlander equation and CONWEP. The results of these simulations provide sufficient encouragement to pursue the multi-scale modeling of STFs types of materials.

2B3: Reliability Assessment and Warranty Forecasting of Repairable Systems
Quad members: Zissimos P. Mourelatos (PI), Vijitashwa Pandey (co-PI), Themistoklis Koutsellis (Oakland Univeristy); Matt Castanier (U.S. Army TARDEC); Mohammad Hijawi (Fiat Chrysler Automobiles)

        Most engineering systems are repairable. Their components can be renewed or repaired if system failure occurs, to put the system back into service. In this work, a Generalized Renewal Process (GRP) model quantifies the reliability of a repairable system based on the concept of virtual or effective age. The model accounts for repair assumptions such as “same-as-old,” “good-as-new,” “better-than-old-but-worse-than-new” and “worse-than-old,” and is suitable for reset and depot maintenance strategies as well as warranty prediction and forecasting of vehicle fleets. In warranty forecasting, it is desired to predict the Expected Number of Failures (ENF) after a censoring time using collected failure data before the censoring time. We will present a forecasting method to predict the ENF of a repairable system using observed data. First, a GRP model is calibrated using the observed data and then the model is used to forecast failures. All developments will be demonstrated using vehicle production data.

2B4: Restraint System Optimization for Occupant Protection in Tactical Vehicles: Full Vehicle Crash Tests
Quad members: Jingwen Hu (PI), Matthew Reed (Co-PI) (University of Michigan); Zissimos Mourelatos, Dorin Drignei (Oakland University); Rebekah Gruber, David Clark, Risa Scherer (U.S. Army TARDEC); Marianne Kump, Brian Hansen (TAKATA)

        The objective of this study is to optimize the restraint systems for tactical vehicle occupants using an innovative combination of simulation and physical testing guided by calibration-based optimization. In the previous years of this study, two full vehicle crash tests in frontal and rollover impacts, over 50 sled tests, and hundreds of FE simulations were conducted to optimize seatbelt and airbag designs for occupants with different sizes and military gear configurations. In the last year of this study, we focused on conducting full vehicle frontal and rollover crash tests with optimized restraint systems. Comparisons between the tests with the baseline and optimized restraint systems clearly demonstrated the benefit of using airbags and advanced seatbelt technologies for protecting tactical vehicle occupants.