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Topology optimization is a branch of structural optimization which solves an optimal material distribution problem. The resulting structural topology, for a given set of boundary conditions and constraints, has an optimal performance (e.g. minimum compliance). Conventional 3D topology optimization algorithms achieve quality optimized results; however, it is an extremely computationally intensive task which is, in general, impractical and computationally unachievable for real-world structural optimal design processes. Therefore, the current development of rapid topology optimization technology is experiencing a major drawback. To address the issues, a new approach is presented to utilize the powerful abilities of large deep learning models to replicate this design process for 3D structures. Adversarial models, primarily Wasserstein Generative Adversarial Networks (WGAN), are constructed which consist of 2 deep convolutional neural networks (CNN) namely, a discriminator and a generator.

In recent years, many motorsports have been developing competitions based on electric vehicles. The demanding performance requires the battery pack to have the perfect balance between energy, power, and weight. This research paper presents a systematic methodology for the initial design of the battery pack (size and cell chemistry) by statistically analyzing the characteristics of the mission profile. The power profile for the battery pack of a motorsport vehicle can be estimated by considering the duty cycle of a racing car using the technical and sporting regulations and vehicle parameters. In this paper, many statistical metrics correlated to this power profile have been defined and analyzed (such as the max, mean, and standard deviation of the power profile, the total energy consumed, and the expected heat generation). These metrics have been used to estimate the cell energy and power density requirement and the pack sizing considering the weight constraints.

The EcoCAR 2: Plugging into the Future team at the Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 50 miles of all-electric range. The vehicle features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 75 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report details the rigorous design process followed by the Ohio State team during Year 1 of the competition. The design process includes identifying the team customer's needs and wants, selecting an overall vehicle architecture and completing detailed design work on the mechanical, electrical and control systems. This effort was made possible through support from the U.S.

The design of a performance hybrid electric vehicle includes a wide range of architecture possibilities. A large part of the design process is identifying reasonable vehicle architectures and vehicle performance capabilities. The Ohio State University EcoCAR 3 team designed a plug-in hybrid electric vehicle (PHEV) post-transmission parallel 2016 Chevrolet Camaro. With the end-goal of reducing the environmental impact of the vehicle, the Ohio State Camaro has been designed with a 44-mile all-electric range. It also features an 18.9 kWh Li-ion energy storage system, a 119 kW 2.0L GDI I4 engine that runs on 85% ethanol (E85) fuel, a 5-speed automated manual transmission, and a 150 kW peak electric machine. This report details the design and modeling process followed by the Ohio State team during Year 1 of the competition. The process included researching the customer needs of the vehicle, determining team design goals, initial modeling, and selecting a vehicle architecture.

Two major concerns have inhibited the use of natural laminar flow (NLF) for viscous drag reduction on production aircraft. These are the concerns of achieveability of NLF on practical airframe surfaces, and maintainability in operating environments. Previous research in this area left a mixture of positive and negative conclusions regarding these concerns. While early (pre-1950) airframe construction methods could not achieve NLF criteria for waviness, several modern construction methods (composites for example) can achieve the required smoothness. This paper presents flight experiment data on the achieveability and maintainability of NLF on a high-performance, single-propeller, composite airplane, the Bellanca Skyrocket II. The significant contribution of laminar flow to the performance of this airplane was measured. Observations of laminar flow in the propeller slipstream are discussed, as are the effects of insect contamination on the wing.

Combined active and passive damping is a recent trend that can be an effective solution to challenging NVH problems, especially for lightweight vehicle components that demand advanced noise and vibration treatments. Compact patches are of particular interest due to their small size and cost, however, improved modeling techniques are needed at the design stage for such methods. This paper presents a refined modeling procedure for side-by-side active and passive damping patches applied to thin, plate-like, powertrain casing structures. As an example, a plate with fixed boundaries is modeled as this is representative of real-life transmission covers which often require damping treatments. The proposed model is then utilized to examine several cases of active and passive patch location, and vibration reduction is determined in terms of insertion loss for each case.

The parameters determining shift quality control in automatic transmissions are determined as part of the calibration of the transmission control. The resulting control system typically has three components: feedforward control, where the control output is determined before a gearshift; feedback control, where the control output is determined during the gearshift based on sensed feedback; and learning control (adaptation), where the feedforward or feedback controller parameters are modified after the current gearshift has ended and before the next similar gearshift begins. Gearshifts involving the same ratio change are referred to here as similar gearshifts, though such gearshifts may involve differences in other variables such as vehicle speed or engine torque.

The EcoCAR 2: Plugging into the Future team at The Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 44 miles of all-electric range. The vehicle features an 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes. This is made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 50 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This paper details three years of modeling and simulation development for the OSU EcoCAR 2 vehicle. Included in this paper are the processes for developing simulation platform and model requirements, plant model and soft ECU development, test development and validation, automated regression testing, and controls and calibration optimization.

Improvements in highway fuel economy require clever design and novel methods to reduce the drag coefficient. The integration of active flow control devices into vehicle design shows promise for greater reductions in drag coefficient. This paper examines the use of fluidic oscillators for separation control at the rear of an Ahmed vehicle model. A fluidic oscillator is a simple device that generates a sweeping jet output, similar to some windshield wiper spray nozzles, and is increasingly recognized as an efficient means to control separation. In this study, fluidic oscillators were used to blow unsteady air jets and control flow separation on rear boat-tail flaps, achieving drag reductions greater than 70 counts. The method appears to scale favorably to a larger model, and realistic effects such as a rolling road appear to have a small impact on the oscillator's control authority.

Future aircraft will demand a significant amount of electrical power to drive primary flight control surfaces. The electrical system architecture needed to source these flight critical loads will have to be resilient, autonomous, and fast. Designing and ensuring that a power system architecture can meet the load requirements and provide power to the flight critical buses at all times is fundamental. In this paper, formal methods and linear temporal logic are used to develop a contactor control strategy to meet the given specifications. The resulting strategy is able to manage multiple contactors during different types of generator failures. In order to verify the feasibility of the control strategy, a real-time simulation platform is developed to simulate the electrical power system. The platform has the capability to test an external controller through Hardware in the Loop (HIL).

The reliable operation of power systems on the lunar surface is crucial for critical research activities and supporting life. These systems are standalone or interconnected grids that integrate intermittent power sources and distributed energy storage. Lunar microgrids must be highly reliable, reconfigurable, and efficient. To meet these requirements, we propose the flexible DC energy router (FeDER), a modular and scalable power management unit for interconnected lunar DC microgrids. The FeDER integrates local energy storage and addresses various microgrid power management needs such as fault management, stability enhancement, power flow regulation, and power quality improvement. The lunar DC microgrids' design, protection, and control are achieved using a three-layered approach: (1) graph theory, (2) energy management system, and (3) smart resistor control. The lunar power grid architecture is introduced and the FeDER stability enhancement is implemented in the OPAL-RT platform.