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Although the design phase can account for a sizable amount of the resources consumed during the product realization process, the time and costs associated with the design process are often neglected when making design decisions. To investigate this issue, we define a process-centric decision model in which the design-phase consumption of resources, such as time and money, is explicitly modeled. While it is clear that the utility of a design is almost always directly impacted by the monetary costs of the design process, our decision model also accounts for the fact that the profit earned by a product depends strongly on its launch date. The decision model allows us thus to consider the trade-off between the time necessary for analysis and the improvement in product quality that results from the analysis. The decision model is sufficiently generic that almost any set of beliefs about the alternatives or analyses, as well as any utility-based preference structure can be modeled.

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.

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.

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.

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.

This paper looks at a method for decomposing a manufactured product into what is called an “activity space.” The method uses an activity based costing scheme to structure the model and organize the information. It is discussed how the activity space is used to perform sustainability assessments of a manufactured product and the manufacturing process from different viewpoints and perspectives. The way in which the activity space is used to perform an assessment from several viewpoints is discussed.

Several research institutions and universities have taken on the challenge of providing solutions for accessible and universally designed workplace accommodations with a focus on people with disabilities. Accessible Design is a subset of what is termed Universal Design. Where Universal Design covers the design of products, systems and environments for all people and encompasses all design principles, Accessible Design focuses on principles that extend the standard design process to those people with some type of performance limitation. In order for individuals with disabiltities to gain better access to the work environments and the products that facilitate independence, health, safety, and social participation a multi-disciplined approach to the research is needed to identify needs and challenges of the targeted population.

Battery modeling is of major concern for Hybrid Electric Vehicle (HEV) and Electric vehicle (EV) modeling. The major issue lies in characterizing the battery power output in relation to battery's State of Charge (SOC) in various application conditions. In particular, the challenge is associated with the difficulty that the characteristic parameters of the battery, i.e. the accurate data on the open circuit voltage and the internal resistance are hardly obtainable in practical conditions. In this paper, a battery capacity representation and a practical way of battery modeling is introduced for simulation model development based on the experimental data. A realistic way of battery SOC representation is generated from the battery output data. Empirical formulation is derived from the data to correlate the battery current, voltage output with the battery SOC.

In gasoline direct injection engines, fuel is injected into the port walls and the valve. During the engine startup cycle, the temperature of these parts is not adequate to evaporate all the fuel that impacts the walls. As a result, a fraction of the injected fuel does not contribute to the combustion cycle. This fraction forms fuel puddles (wall-wetting) and a portion of it passes to the crankcase. The efficiency of the engine during the startup cycle is decreased and hydrocarbon emissions increased. It is obvious that a control strategy is necessary to minimize the effects of this transient performance of the engine. This paper investigates a modeling framework for the valve, and simulation results validate model performance when compared to available experimental data. The simulation studies lead to a conceptual control design, which is briefly outlined.

The Georgia Tech EcoCAR 3 team’s selection of a parallel hybrid electric vehicle (HEV) architecture for the EcoCAR 3 competition is presented in detail, with a focus on the team’s modeling and simulation efforts and how they informed the team’s architecture selection and subsequent component decisions. EcoCAR 3, sponsored by the United States Department of Energy and General Motors, is the latest in a series of Advanced Vehicle Technology Competitions (AVTCs) and features 16 universities from the United States and Canada competing to transform the 2016 Chevrolet Camaro into a hybrid electric American performance vehicle. Team vehicles will be scored on performance, emissions, fuel economy, consumer acceptability, and more over the course of the four-year competition. During the first year, the Georgia Tech team considered numerous component combinations and HEV architectures, including series RWD and AWD, parallel, and power-split.

The recent development of electric vehicles creates a new area of interest regarding their potential impacts on natural resource and energy networks. Water consumption is of particular interest, as water scarcity becomes a growing problem in many regions of the world. Water usage can be traced to the production of gasoline, as well as electricity, for regular operation of these vehicles. This paper focuses on the development of a framework to analyze the amount of water consumed in the operation of both conventional and electric vehicles. Using the Systems Modeling Language, a model was developed based on the water consumed directly in energy generation and processing as well as water consumed in obtaining and processing a vehicle's fuels. This model and framework will use the above water consumption breakdown to examine conventional and electric vehicles in metropolitan Atlanta to assess their impacts on that and other urban networks.

The atomization and initial spray formation processes in direct injection engines are not well understood due to the experimental and computational challenges associated with resolving these processes. Although different physical mechanisms, such as aerodynamic-induced instabilities and nozzle-generated turbulence and cavitation, have been proposed in the literature to describe these processes, direct validation of the theoretical basis of these models under engine-relevant conditions has not been possible to date. Recent developments in droplet sizing measurement techniques offer a new opportunity to evaluate droplet size distributions formed in the central and peripheral regions of the spray. There is therefore a need to understand how these measurements might be utilized to validate unobservable physics in the near nozzle-region.

This study investigates the role of turbulent-chemistry interaction in simulations of diesel spray combustion phenomena after end-of-injection (EOI), using the commercially-available CFD code CONVERGE. Recent experimental and computational studies have shown that the spray flame dynamics and mixture formation after EOI are governed by turbulent entrainment, coupled with rapid evolution of the thermo-chemical state of the mixture field. A few studies have shown that after EOI, mixtures between the injector nozzle and the lifted diffusion flame can ignite and appear to propagate back towards the injector nozzle via an auto-ignition reaction sequence; referred to as “combustion recession”.

This presentation is an assessment of the turbulence-stress scale-similarity in an IC engine, which is used for modeling subgrid dissipation in LES. Residual stresses and Leonard stresses were computed after applying progressively smaller spatial filters to measured and simulated velocity distributions. The velocity was measured in the TCC-II engine using planar and stereo PIV taken in three different planes and with three different spatial resolutions, thus yielding two and three velocity components, respectively. Comparisons are made between the stresses computed from the measured velocity and stress computed from the LES resolved-scale velocity from an LES simulation. The results present the degree of similarity between the residual stresses and the Leonard stresses at adjacent scales. The specified filters are systematically reduced in size to the resolution limits of the measurements and simulation.

In this paper, the relationship between uncertainty and sets of alternatives in engineering design is investigated. In sequential decision making, each decision alternative actually consists of a set of design alternatives. Consequently, the decision-maker can express his or her preferences only imprecisely as a range of expected utilities for each decision alternative. In addition, the performance of each design alternative can be characterized only imprecisely due to uncertainty from limited data, modeling assumptions, and numerical methods. The approach presented in this paper recognizes the presence of both imprecision and sets in the design process by focusing on incrementally eliminating decision alternatives until a small set of solutions remains. This is a fundamental shift from the current paradigm where the focus is on selecting a single decision alternative in each design decision.

While a number of important attempts have been made to describe characteristics of an intersection purely in mathematical terms, the most fruitful research from a practical standpoint has utilized simulation. This paper reports the results of research in which a four-way stop intersection was simulated on a digital computer. Inputs to the program were based on field studies at three intersections in metropolitan Atlanta using mathematical models and Monte Carlo techniques. Field data were taken with the aid of a spring wound Esterline-Angus 20-pen event recorder and time lapse movies. The simulation model was used to study the effectiveness of the four-way stop at various approach volumes and turning movement combinations. Results of experiments conducted on the simulation model are given by graphs showing the relationship between traffic volumes and average delay, per cent delayed, and average queue length.

A hybrid electric vehicle (HEV) simulation has been developed for an electric-assist parallel configuration vehicle, at the University of Tennessee, Knoxville. The model was developed in MATLAB/SIMULINK using ADVISOR, a HEV simulation model developed by the National Renewable Energy Laboratory. The Neon simulation model implements a power control strategy using throttle position as the primary input. It incorporates other features of HEV power control such as battery regeneration and regenerative braking. A practical way of battery modeling is incorporated into this model. The model also simulates the vehicle operation as a pure electric vehicle (EV) or as a conventional vehicle (heat engine only). By using the Neon model, the performance of the vehicle has been analyzed using parametric analysis of the vehicle components and power control parameters. Recommendations are given for improving the design based on the simulation results.