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We present a new interval-based formulation for the static analysis of plane stress/strain problems with uncertain parameters in load, material and geometry. We exploit the Interval Finite Element Method (IFEM) to model uncertainties in the system. Overestimation due to dependency among interval variables is reduced using a new decomposition strategy for the structural stiffness matrix and the nodal equivalent load vector. Primary and derived quantities follow from minimization of the total energy and they are solved simultaneously and with the same accuracy by means of Lagrangian multipliers. Two different element assembly strategies are introduced in the formulation: one is Element-by-Element, and the other resembles conventional assembly. In addition, we implement a new variant of the interval iterative enclosure method to obtain outer and inner solutions. Numerical examples show that the proposed interval approach guarantees to enclose the exact system response.

This work contributes to the understanding of physical mechanisms that control flashback, or more appropriately combustion recession, in diesel sprays. A large dataset, comprising many fuels, injection pressures, ambient temperatures, ambient oxygen concentrations, ambient densities, and nozzle diameters is used to explore experimental trends for the behavior of combustion recession. Then, a reduced-order model, capable of modeling non-reacting and reacting conditions, is used to help interpret the experimental trends. Finally, the reduced-order model is used to predict how a controlled ramp-down rate-of-injection can enhance the likelihood of combustion recession for conditions that would not normally exhibit combustion recession. In general, fuel, ambient conditions, and the end-of-injection transient determine the success or failure of combustion recession.

In early phases of conceptual design stages for developing a new car in the modern automobile industry, the lack of systematic methodology to efficiently converge to an agreement between the aesthetics and aerodynamic performance tremendously increases budget and time. During these procedures, one of the most important tasks is to create geometric information which is versatilely morphable upon the demands of both of stylists and engineers. In this perspective, this paper proposes a Spline-based Modeling Algorithm (SMA) to implement into performing aerodynamic design optimization research based on CFD analysis. Once a 3-perspective schematic of a car is given, SMA regresses the backbone boundary lines by using optimum polynomial interpolation methods with the best goodness of fit, eventually reconstructing the 3D shape by linearly interpolating from the extracted boundaries minimizing loss of important geometric features.

Modeling and simulation are commonly used in all stages of the design process. This is particularly vital to the success of systems engineering projects where the system under consideration is complex and involves interactions between many interdisciplinary subsystems. In the refining stages of the design process (after concept selection), models and simulations can be used to refine and optimize a system with respect to the decision maker’s objectives. In this paper, a dynamic model of a hydraulic backhoe serves as a test-bed for a large-scale sensitivity analysis and subsequent optimization of the most significant design parameters. The model is optimized under uncertainty with respect to a multi-attribute utility function that includes fuel consumption, cost of the key components, and machine performance.

Suspension system dynamics can be obtained by various methods and vehicle design has gained great advantages over the dynamics analysis. By employing the new Udwadia-Kalaba equation, we endeavor some attempts on its application to dynamic modeling of vehicle suspension systems. The modeling approach first segments the suspension system into several component subsystems with kinematic constraints at the segment points released. The equations of motion of the unconstrained subsystems are thus easily obtained. Then by applying the second order constraints, the suspension system dynamics is then obtained. The equations are of closed-form. Having the equations obtained, we then show its application on dynamical load analysis. The solutions for the dynamical loads at interested hard points are obtained. We use the double wishbone suspension to show the systematic approach is easy handling.

Power-split hybrid-electric vehicles (HEVs) employ two power paths between the internal combustion (IC) engine and the driven wheels routed through gearing and electric machines (EMs) composing an electrically variable transmission (EVT). The EVT allows IC engine control such that rotational speed can be independent of vehicle speed at all times. By breaking the rigid mechanical connection between the IC engine and the driven wheels, the EVT allows the IC engine to operate in the most efficient region of its characteristic brake specific fuel consumption (BSFC) map. If the most efficient IC engine operating point produces more power than is requested by the driver, the excess IC engine power can be stored in the energy storage system (ESS) and used later. Conversely, if the most efficient IC engine operating point does not meet the power request of the driver, the ESS delivers the difference to the wheels through the EMs.

This paper presents a forward-looking simulation (FLS) approach for the front wheel drive (FWD) General Motors Allison Hybrid System II (GM AHS-II). The supervisory control approach is based on a dynamic programming-informed Equivalent Cost Minimization Strategy (ECMS). The controller development uses backward-looking simulations (BLS), which execute quickly by neglecting component transients while assuming exact adherence to a specified drive cycle. Since ECMS sometimes prescribes control strategies with rapid component transients, its efficacy remains unknown until these transients are modeled. This is addressed by porting the ECMS controller to a forward-looking simulation where component transients are modeled in high fidelity. Techniques of implementing the ECMS controller and commanding the various power plants in the GM AHS-II for FLS are discussed.

With the advent of autonomous vehicles, the human driver’s attention will slowly be relinquished from the driving task. It will allow drivers to participate in more non-driving related activities, such as engaging with information and entertainment systems. However, the automated driving system would need to notify the driver of upcoming points-of-interest on the road when the driver’s attention is focused on their screen rather than on the road or driving display. In this paper, we investigated whether providing directional alerts for an upcoming point-of-interest (POI) in or around the user’s active screen can augment their ability in relocating their visual attention to the POI on the road when traveling in a vehicle with Conditional Driving Automation. A user study (N = 15) was conducted to compare solutions for alerts that presented themselves in the participants’ central and peripheral field of view.

In order to improve understanding of the primary atomization process for diesel-like sprays, a collaborative experimental and computational study was focused on the near-nozzle spray structure for the Engine Combustion Network (ECN) Spray D single-hole injector. These results were presented at the 5th Workshop of the ECN in Detroit, Michigan. Application of x-ray diagnostics to the Spray D standard cold condition enabled quantification of distributions of mass, phase interfacial area, and droplet size in the near-nozzle region from 0.1 to 14 mm from the nozzle exit. Using these data, several modeling frameworks, from Lagrangian-Eulerian to Eulerian-Eulerian and from Reynolds-Averaged Navier-Stokes (RANS) to Direct Numerical Simulation (DNS), were assessed in their ability to capture and explain experimentally observed spray details. Due to its computational efficiency, the Lagrangian-Eulerian approach was able to provide spray predictions across a broad range of conditions.

Spray processes, such as primary breakup, play an important role for subsequent combustion processes and emissions formation. Accurate modeling of these spray physics is therefore key to ensure faithful representation of both the global and local characteristics of the spray. However, the governing physical mechanisms underlying primary breakup in fuel sprays are still not known. Several theories have been proposed and incorporated into different engineering models for the primary breakup of fuel sprays, with the most widely employed models following an approach based on aerodynamically-induced breakup, or more recently, based on liquid turbulence-induced breakup. However, a complete validation of these breakup models and theories is lacking since no existing measurements have yielded the joint liquid mass and drop size distribution needed to fully define the spray, especially in the near-nozzle region.

The blade crossing event of a coaxial counter-rotating rotor is a potential source of noise and impulsive blade loads. Blade crossings occur many times during each rotor revolution. In previous research by the authors, this phenomenon was analyzed by simulating two airfoils passing each other at specified speeds and vertical separation distances, using the compressible Navier-Stokes solver OVERFLOW. The simulations explored mutual aerodynamic interactions associated with thickness, circulation, and compressibility effects. Results revealed the complex nature of the aerodynamic impulses generated by upper/lower airfoil interactions. In this paper, the coaxial rotor system is simulated using two trains of airfoils, vertically offset, and traveling in opposite directions. The simulation represents multiple blade crossings in a rotor revolution by specifying horizontal distances between each airfoil in the train based on the circumferential distance between blade tips.

A Stagnation Point Actuator is used to control the lateral dynamics of vortices generated over a sharp-pointed forebody, at high angles of attack, and the resulting rolling moment is studied. Effective roll control is demonstrated, including the ability to suppress the wing rock phenomenon. Piecewise-linear transfer functions are developed from experimental data for the changes in roll moment and pressure difference with actuator frequency content. These transfer functions are reduced to compact form in the frequency domain, and then to a time-domain model using 2 gains and 2 time scales. The roll response is classified according to angle of attack range. Some long time scales are observed in the surface pressure, velocity field and rolling moment, making the response relatively insensitive to speed. Thus over substantial speed ranges, linear transfer functions are shown to effectively describe the roll response to motion of the Stagnation Point Actuator.

The wind-driven dynamic manipulator is a device which uses the wind tunnel freestream energy to drive multi-axis maneuvers of test models. This paper summarizes work performed using the device in several applications and discusses current work on characterizing the aerodynamics of an X-38 vehicle model in pitch-yaw maneuvers. Previous applications in flow visualization, adaptive control and linear-domain parameter identification are now extended to multi-axis inverse force and moment measurement over large ranges of attitude. A pitch-yaw-roll version is operated with active roll to measure forces and moments during maneuvers. A 3-D look-up table generated from direct force calibration allows operation of the manipulator through nonlinear regimes where control wing stall and boom wake-wing interactions are allowed to occur. Hybrid designs combining conventional and wind-driven degrees of freedom are discussed.

The High Speed Civil Transport (HSCT), a supersonic commercial transport currently under development, presents several challenges to traditional conceptual design. The current historical database used by many commercial transport design processes only include data for subsonic transports and therefore does not apply to innovative new configurations such as the HSCT. Therefore, physics-based, preliminary design tools must be used to model the characteristics of advanced aircraft in conceptual sizing routines. In addition, the evaluation of the aircraft design space often requires the analysis of many configurations in order to assess the impact of design constraints and determine the attainable range of system level metrics, a process which is very time consuming in both modeling and computer run time.

Neural network augmented model inversion control is used to provide a civilian tilt-rotor aircraft with consistent response characteristics throughout its operating envelope, including conversion flight. The implemented response types are Attitude Command Attitude Hold in the longitudinal channel, and Rate Command Attitude Hold about the roll and yaw axes. This article describes the augmentation in the roll channel and the augmentation for the yaw motion including Heading Hold at low airspeeds and automatic Turn Coordination at cruise flight. Conventional methods require extensive gain scheduling with tilt-rotor nacelle angle and airspeed. A control architecture is developed that can alleviate this requirement and thus has the potential to reduce development time. It also facilitates the implementation of desired handling qualities, and permits compensation for partial failures.

In this study we identify components of a typical biodiesel fuel and estimate both their individual and mixed thermo-physical and transport properties. We then use the estimated mixture properties in computational simulations to gauge the extent to which combustion is modified when biodiesel is substituted for conventional diesel fuel. Our simulation studies included both conventional diesel combustion (DI) and premixed charge compression ignition (PCCI). Preliminary results indicate that biodiesel ignition is significantly delayed due to slower liquid evaporation, with the effects being more pronounced for DI than PCCI. The lower vapor pressure and higher liquid heat capacity of biodiesel are two key contributors to this slower rate of evaporation. Other physical properties are more similar between the two fuels, and their impacts are not clearly evident in the present study.

A plug-in hybrid electric vehicle (PHEV) design with design parameters electric motor size, engine size, battery capacity, and battery chemistry type, is optimized with minimum cost as a measure of merit. The PHEV is required to meet a fixed set of performance constraints consisting of 0-60 mph acceleration, 50-70 mph acceleration, 0-30 mph acceleration in all electric operation, top speed, grade ability, and all electric range. The optimization is carried out for values of all electric range of 10, 20, and 40 miles. The social and economic impacts of the optimum designs in terms of reduced gasoline consumption and carbon emissions reduction are calculated. Argonne National Laboratory's Powertrain Systems Analysis Toolkit is used to simulate the performance and fuel economy of the PHEV designs. The costs of different PHEV components and the present value of battery replacements over the vehicle's life are used to determine the design's drivetrain cost.

The design of complex systems, such as commercial aircraft, has drastically changed since the middle 1970's. Budgetary and airline requirements have forced many aerospace companies to reduce the amount of time and monetary investments in future revolutionary concepts and design methods. The current NASA administration has noticed this shift in aviation focus and responded with the “Three Pillars for Success” program. This program is a roadmap for the development of research, innovative ideas, and technology implementation goals for the next 20 years. As a response to this program, the Aerospace Systems Design Laboratory at Georgia Tech is developing methods whereby forecasting techniques will aid in the proper assessment of future vehicle concepts. This method is called Technology Impact Forecasting (TIF). This method is applied to a medium-range, intra-continental, commercial transport concept.

This paper critically evaluates the use of Neural Networks (NNs) as metamodels for design applications. The specifics of implementing a NN approach are researched and discussed, including the type and architecture appropriate for design-related tasks, the processes of collecting training and validation data, and training the network, resulting in a sound process, which is described. This approach is then contrasted to the Response Surface Methodology (RSM). As illustrative problems, two equations to be approximated and a real-world problem from a Stability and Controls scenario, where it is desirable to predict the static longitudinal stability for a High Speed Civil Transport (HSCT) at takeoff, are presented. This research examines Response Surface Equations (RSEs) as Taylor series approximations, and explains their high performance as a proven approach to approximate functions that are known to be quadratic or near quadratic in nature.

General Motors has introduced a Two-Mode Transmission (2-MT) that provides significant improvements over the Toyota THS-II transmission. These improvements are achieved by employing additional planetaries with clutches and brakes to switch from a Mode-1 to Mode-2 as vehicle speed increases. In addition the 2-MT has four fixed-gear ratios that provide for a purely mechanical energy path from the IC engine to the driven wheels with the electric machines also able to provide additional driving torque. The purpose of this present paper is to extend the methodology in a previous paper [1] to include the 2-MT, thereby presenting an analytic foundation for its operation. The main contribution in this analysis is in the definition of dimensionless separation factors, defined in each mode that govern the power split between the parallel mechanical and electrical energy paths from the IC engine to the driven wheels.