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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.

Turboelectric propulsion is a technology that can potentially reduce aircraft noise, increase fuel efficiency, and decrease harmful emissions. In a turbo-electric system, the propulsor (fans) is no longer connected to the turbine through a mechanical connection. Instead, a superconducting generator connected to a gas turbine produces electrical power which is delivered to distributed fans. This configuration can potentially decrease fuel burn by 10% [1]. One of the primary challenges in implementing turboelectric electric propulsion is designing the power distribution system to transmit power from the generator to the fans. The power distribution system is required to transmit 40 MW of power from the generator to the electrical loads on the aircraft. A conventional aircraft distribution cannot efficiently or reliably transmit this large amount of power; therefore, new power distribution technologies must be considered.

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.

As an element of a design optimization study of high speed civil transport (HSCT), response surface equations (RSEs) were developed with the goal of accurately predicting the sideline, takeoff, and approach noise levels for any combination of selected design variables. These RSEs were needed during vehicle synthesis to constrain the aircraft design to meet FAR 36, Stage 3 noise levels. Development of the RSEs was useful as an application of response surface methodology to a previously untested discipline. Noise levels were predicted using the Aircraft Noise Prediction Program (ANOPP), with additional corrections to account for inlet and exhaust duct lining, mixer-ejector nozzles, multiple fan stages, and wing reflection. The fan, jet, and airframe contributions were considered in the aircraft source noise prediction.

A supersonic channel airfoil (SCA) concept that can be applied to the leading edges of wings, tails, fins, struts, and other appendages of aircraft, atmospheric entry vehicles and missiles in supersonic flight for drag reduction is described. It is designed to be beneficial at conditions in which the leading edge is significantly blunted and the Mach number normal to the leading edge is supersonic. The concept is found to result in significantly reduced wave drag and total drag (including skin friction drag) and significantly increased L/D. While this reduction over varying flight conditions has been quantified, some leading edge geometries result in adverse increases in peak heat transfer rates. To evaluate the effectiveness of SCAs in reducing drag without paying any penalties in other areas like lifting capacity, heating rates or enclosed volume, the design space was studied in greater detail using MDO methods.

This paper outlines the design of a part transport and loading/unloading automation system for a cylindrical die thread roller, enumerating many of the design decisions encountered. Specifically, a transport tray system is proposed and prototyped as a benchmark for factory automation. Details of an automation system which will interface with the proposed transport tray system are discussed. A gripping system which accommodates a wide variety of fastener head styles is developed to work in conjunction with the tray concept, and prototyped with favorable results.

Trail-Braking (TB) is a common cornering technique used in rally racing to negotiate tight corners at (moderately) high speeds. In a previous paper by the authors it has been shown that TB can be generated as the solution to the minimum-time cornering problem, subject to fixed final positioning of the vehicle after the corner. A TB maneuver can then be computed by solving a non-linear programming (NLP). In this work we formulate an optimization problem by relaxing the final positioning of the vehicle with respect to the width of the road in order to study the optimality of late-apex trajectories typically followed by rally drivers. We test the results on a variety of corners. The optimal control inputs are approximated by simple piecewise linear input profiles defined by a small number of parameters. It is shown that the proposed input parameterization can generate close to optimal TB along the various corner geometries.

An integrated, multidisciplinary environment of a tactical aircraft platform has been created by leveraging the powerful capabilities of both MATLAB/Simulink and Numerical Propulsion System Simulation (NPSS). The overall simulation includes propulsion, power, and thermal management subsystem models, which are integrated together and linked to an air vehicle model and mission profile. The model has the capability of tracking temperatures and performance metrics and subsequently controlling characteristics of the propulsion and thermal management subsystems. The integrated model enables system-level trade studies involving the optimization of engine bleed and power extraction and thermal management requirements to be conducted. The simulation can also be used to examine future technologies and advanced thermal management architectures in order to increase mission capability and performance.

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 FutureTruck Team has designed a strong parallel split-hybrid powertrain for the model year 2002 Ford Explorer SUV. The modified powertrain uses a Lincoln LS 3.0L, V-6, DOHC, aluminum engine driving the rear axle. An AC-150 from AC Propulsion is coupled to the front wheels through a 3.75:1 Auburn Gear speed reducer. This split-hybrid structure fits well into the Explorer and is to manufacture. The interior cabin has been maintained in a stock configuration by carefully integrating the added instrumentation and electric drive controls into the dash and console. The toque-blending hybrid electric control is designed to be charge sustaining such that the refueling procedures match those of the stock vehicle. When fully operational, this powertrain is expected to yield a net 25% increase in fuel efficiency while lowering emissions without any sacrifice in customer acceptability.

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.

Several approaches to robust design have been proposed in the past. Only few acknowledged the paradigm shift from performance based design to design for cost. The incorporation of economics in the design process, however, makes a probabilistic approach to design necessary, due to the inherent ambiguity of assumptions and requirements as well as the operating environment of future aircraft. The approach previously proposed by the authors, linking Response Surface Methodology with Monte Carlo Simulations, has revealed itself to be cumbersome and at times impractical for multi-constraint, multi-objective problems. In addition, prediction accuracy problems were observed for certain scenarios that could not easily be resolved. Hence, this paper proposes an alternate approach to probabilistic design, which is based on a Fast Probability Integration technique.

This paper attempts to assess the benefits of a unique distributed propulsion concept, known as the Multi-Gas Generator Fan (MGGF) system, over conventional turbofan engines on civilian vertical takeoff and landing (VTOL) applications. The MGGF-based system has shown the potential to address the fundamental technical challenge in designing a VTOL aircraft: the significant mismatch between the power requirements at lift-off/hover and cruise. Vehicle-level performance and sizing studies were implemented using the Grumman Design 698 tilt-nacelle V/STOL aircraft as a notional personal air vehicle (PAV), subjected to hypothetical single engine failure (SEF) emergency landing requirements and PAV mission requirements.

A design process is formulated and implemented for the taxonomy selection and system-level optimization of an Efficient Multi-Mach Aircraft Current Technology Concept and an Advanced Concept. Concept space exploration of taxonomy alternatives is performed with multi-objective genetic algorithms and a Powell’s method scheme for vehicle optimization in a multidisciplinary modeling and simulation environment. A dynamic sensitivity visualization analysis tool is generated for the Advanced Concept with response surface equations.

A multidisciplinary design study considering the impact of Active Aeroelastic Wing (AAW) technology on the structural wing weight of a lightweight fighter concept is presented. The study incorporates multidisciplinary design optimization (MDO) and response surface methods to characterize wing weight as a function of wing geometry. The study involves the sizing of the wing box skins of several fighter configurations to minimum weight subject to static aeroelastic requirements. In addition, the MDO problem makes use of a new capability, trim optimization for redundant control surfaces, to accurately model AAW technology. The response surface methodology incorporates design of experiments, least squares regression, and makes use of the parametric definition of a structural finite element model and aerodynamic model to build response surface equations of wing weight as a function of wing geometric parameters for both AAW technology and conventional control technology.

A key issue in complex systems design is measuring the ‘goodness’ of a design, i.e. finding a criterion through which a particular design is determined to be the ‘best’. Traditional choices in aerospace systems design, such as performance, cost, revenue, reliability, and safety, individually fail to fully capture the life cycle characteristics of the system. Furthermore, current multi-criteria optimization approaches, addressing this problem, rely on deterministic, thus, complete and known information about the system and the environment it is exposed to. In many cases, this information is not be available at the conceptual or preliminary design phases. Hence, critical decisions made in these phases have to draw from only incomplete or uncertain knowledge. One modeling option is to treat this incomplete information probabilistically, accounting for the fact that certain values may be prominent, while the actual value during operation is unknown.

Hybrid-electric gas turbine generators are considered a promising technology for more efficient and sustainable air transportation. The Ohio State University is leading the NASA University Leadership Initiative (ULI) Electric Propulsion: Challenges and Opportunities, focused on the design and demonstration of advanced components and systems to enable high-efficiency hybrid turboelectric powertrains in regional aircraft to be deployed in 2030. Within this large effort, the team is optimizing the design of the battery energy storage system (ESS) and, concurrently, developing a supervisory energy management strategy for the hybrid system to reduce fuel burn while mitigating the impact on the ESS life. In this paper, an energy-based model was developed to predict the performance of a battery-hybrid turboelectric distributed-propulsion (BHTeDP) regional jet.