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The optimal control of anode H2 concentration in fuel cell is the key performance parameter for efficiency and durability of the fuel cell electric vehicle. Implementation of H2 concentration sensor in fuel processing system is the best option to achieve the optimal control operation, but the vulnerability of the chip in H2 concentration sensor to the moisture has not been overcome and no H2 concentration sensor for vehicle application is present in the world so far. Due to the immaturity of the H2 concentration sensor, a number of researches have been being made to keep the H2 concentration in the anode at certain level without H2 concentration sensors. However the effectiveness of those technologies has not been good to meet the design specification in all the operating range of the various driving cycles and environmental condition.

The National Aeronautics and Space Administration (NASA) is preparing for a manned mission to Mars to test the sustainment of civilization on the planet Mars. This research explores the requirements and feasibility of autonomously producing fuel on Mars for a return trip back to Earth. As a part of NASA’s initiative for a manned trip to Mars, our team’s work creates and analyzes the allocation of resources necessary in deploying a fuel station on this foreign soil. Previous research has addressed concerns with a number individual components of this mission such as power required for fuel station and tools; however, the interactions between these components and the effects they would have on the overall requirements for the fuel station are still unknown to NASA. By creating a baseline discrete-event simulation model in a simulation software environment, the research team has been able to simulate the fuel production process on Mars.

This paper features a distributed environment and the steps taken to incorporate the Virtual Range model into the Virtual Test Bed (VTB) infrastructure. The VTB is a prototype of a virtual engineering environment to study operations of current and future space vehicles, spaceports, and ranges. The High-Level Architecture (HLA) is the main environment. The VTB/HLA implementation described here represents different systems that interact in the simulation of a Space Shuttle liftoff. An example implementation displays the collaboration of a simplified version of the Space Shuttle Simulation Model and a simulation of the Launch Scrub Evaluation Model.

This paper describes the development of a distributed environment for spaceport simulation modeling. This distributed environment is the result of the applications of the High-Level Architecture (HLA) and integration frameworks based on software agents and XML. This distributed environment is called the Virtual Test Bed (VTB). A distributed environment is needed due to the nature of the different models needed to represent a spaceport. This paper provides two case studies: one related to the translation of a model from its native environment and the other one related to the integration of real-time weather.

The future of human exploration in the solar system is contingent on the ability to exploit resources in-situ to produce mission consumables. Specifically, it has become clear that the success of a manned mission to Mars will likely depend on fuel components created on the Martian surface. While several architectures for an unmanned fuel production surface facility on Mars exist in theory, a simulation of the performance and operation of these architectures has not been created. In this paper, the framework describing a simulation of one such architecture is defined. Within this architecture, each component of the base is implemented as a state machine, with the ability to communicate with other base elements as well as a supervisor. An environment supervisor is also created which governs low level aspects of the simulation such as movement and resource distribution, in addition to higher-level aspects such as location selection with respect to operations specific behavior.

Fiber-reinforced plastics (FRPs), produced through injection molding, are increasingly preferred over steel in automotive applications due to their lightweight, moldability, and excellent physical properties. However, the expanding use of FRPs presents a critical challenge: deformation stability. The occurrence of warping significantly compromises the initial product quality due to challenges in part mounting and interference with surrounding parts. Consequently, mitigating warpage in FRP-based injection parts is paramount for achieving high-quality parts. In this study, we present a holistic approach to address warpage in injection-molded parts using FRP. We employed a systematic Design of Experiments (DOE) methodology to optimize materials, processes, and equipment, with a focus on reducing warpage, particularly for the exterior part. First, we optimized material using a mixture design in DOE, emphasizing reinforcements favorable for warpage mitigation.

Operator training using a weapon in a real-world environment is risky, expensive, time-consuming, and restricted to the given environment. In addition, governments are under intense scrutiny to provide security, yet they must also strive for efficiency and reduce spending. In other words, they must do more with less. Virtual simulation, is usually employed to solve these limitations. As the operator is trained to maximize weapon effectiveness, the effectiveness-focused training can be completed in an economical manner. Unfortunately, the training is completed in limited scenarios without objective levels of training factors for an individual operator to optimize the weapon effectiveness. Thus, the training will not be effective. For overcoming this problem, we suggest a methodology on guiding effectiveness-focused training of the weapon operator through usability assessments, big data, and Virtual and Constructive (VC) simulations.

This paper describes a model-based approach to diagnosing electrical faults in electrical power systems. Until recently, model-based reasoning has only been applied to physical systems with static, persistent states, and with parts whose behavior can be expressed combinatorially, such as digital circuits. Our research is one of a handful of recent efforts to apply model-based reasoning to more complex systems, those whose behavior is difficult or impossible to express combinatorially, and whose states change continuously over time. The chosen approach to representation is loosely based on the idea of the equation network proposed in [6]. This requires a more complex component and behavior model than for simpler physical devices. The resulting system is being tested on fault data from the SSM/PMAD power system breadboard being developed at NASA-MSFC [9].

The automotive industry’s journey towards fully autonomous vehicles brings more and more vehicle control systems. Additionally, the reliability and robustness of all these systems must be guaranteed for all road and weather conditions before release into the market. However, the ever-increasing number of such control systems, in combination with the number of road and weather conditions, makes it unfeasible to test all scenarios in real life. Thus, the performance and robustness of these systems needs to be proven virtually, via vehicle simulations. The key challenge for performing such a range of simulations is that the tire performance is significantly affected by the road/weather conditions. An end user must therefore have access to the corresponding tire models. The current solution is to test tires under all road surfaces and operating conditions and then derive a set of model parameters from measurements.

Today, many car manufacturers and their suppliers are very interested in power-operated door handles, known as auto flush door handles. These handles have a distinguishing feature in terms of the way they operate. They are hidden in door skins and deployed automatically when users need to open the door. It is obvious that it is a major exterior styling point that makes customers interested in the vehicles that apply it. To make this auto flush door handle, however, there lie difficulties. First, because there is no sufficient space inside a door, applying these handles can be a constraint in exterior design unless the structures of them are kinematic optimized. The insufficient space can also cause problems in appearance of the handles when they are deployed. The purpose of this study is to establish the kinematic system of auto flush door handle to overcome the exterior handicaps such as the excessive exposure of the internal area on the deployed position.

This study deals with the fatigue life prediction methodology of welding simulation components involving arc welding. First, a method for deriving the cyclic deformation and fatigue properties of the weld metal (that is also called ER70S-3 in AWS, American Welding Standard) is explained using solid bar specimens. Then, welded tube specimens were used with two symmetric welds and subjected to axial, torsion, and combined in-phase and out-of-phase axial-torsion loads. In most previous studies the weld bead’s start/stop were arbitrarily removed by overlapping the starting and stop point. Because it can reduce fatigue data scatter. However, in this study make the two symmetric weld’s start/stops exposed to applying load. Because the shape of the weld bead generated after the welding process can act as a notch (Ex. root notch at weld start / Crater at weld stop) to an applied stress. Accordingly, they were intentionally designed to cause stress concentrations on start/stops.

This paper presents deep learning-based prognostics and health management (PHM) for predicting fractures of an electric propulsion (eP) drivetrain system using real-time CAN signals. The deep learning algorithm, based on autoencoders, resamples time-series signals and converts them into 2D images using recurrence plots (RP). Subsequently, through unsupervised learning of DeepSVDD, it detects anomalies in the converted 2D images and predicts the failure of the system in real-time. Also, reliability analysis based on fracture mechanics was performed using the detected signals and big data. In particular, the severity of the eP drivetrain system is proportional to the maximum shear stress (τmax) in terms of linear elastic fracture mechanics (LEFM) and can be calculated by summarizing the relationship between cracks (a) and the stress intensity factor (KIII).

This study delves into the microstructural and mechanical characteristics of AlSi10Mg alloy produced through the Laser Powder Bed Fusion (L-PBF) method. The investigation identified optimal process parameters for AlSi10Mg alloy based on Volume Energy Density (VED). Manufacturing conditions in the L-PBF process involve factors like laser power, scan speed, hatching distance, and layer thickness. Generally, high laser power may lead to spattering, while low laser power can result in lack-of-fusion areas. Similarly, high scan speeds may cause lack-of-fusion, and low scan speeds can induce spattering. Ensuring the quality of specimens and parts necessitates optimizing these process parameters. To address the low elongation properties in the as-built condition, heat treatment was employed. The initial microstructure of AlSi10Mg alloy in its as-built state comprises a cell structure with α-Al cell walls and eutectic Si.

This paper presents the novel active vibration control (AVC) system that controls vehicle body vibration to reduce the structural borne road noise. As a result of vehicle noise testing in an electric vehicle, the predominant frequency of vehicle body vibration that worsens interior noise is in the range of 150-250Hz. Such vibration in that frequency range, commonly masked in engine vibrations, are hard to neglect for electric vehicles. The vibration source of that frequency is the resonance of tire cavity mode. Resonator or absorption material has been applied inside the tire for the control of cavity noise as a passive method. They require an increment of weight and cost. Therefore, a novel method is necessary. The vibration amplified by resonance of cavity mode is transferred to the vehicle body throughout the suspension system. To reduce the vibration, AVC system is applied to the suspension mount.

Complex aerospace engineering systems require innovative methods for performance monitoring and anomaly detection. The interface of a real-time data stream to a system for analysis, pattern recognition, and anomaly detection can require distributed system architectures and sophisticated custom programming. This paper presents a case study of a simplified interface between Programmable Logic Controller (PLC) real-time data output, signal processing, cloud computing, and tablet systems. The discussed approach consists of three parts: First, the connectivity of real-time data from PLCs to the signal processing algorithms, using standard communication technologies. Second, the interface of legacy routines, such as NASA's Inductive Monitoring System (IMS), with a hybrid signal processing system. Third, the connectivity and interaction of the signal processing system with a wireless and distributed tablet, (iPhone/iPad) in a hybrid system configuration using cloud computing.

As the automotive industry accelerates its virtual engineering capabilities, there is a growing requirement for increased accuracy across a broad range of vehicle simulations. Regarding control system development, utilizing vehicle simulations to conduct ‘pre-tuning’ activities can significantly reduce time and costs. However, achieving an accurate prediction of, e.g., stopping distance, requires accurate tire modeling. The Magic Formula tire model is often used to effectively model the tire response within vehicle dynamics simulations. However, such models often: i) represent the tire driving on sandpaper; and ii) do not accurately capture the transient response over a wide slip range. In this paper, a novel methodology is developed using the MF-Tyre/MF-Swift tire model to enhance the accuracy of ABS braking simulations.

This paper analyzes the leakage magnetic field generated by the Bi-Directional wireless charging system of Electric Vehicle(EV) and confirms the effect of the shielding coil in the Bi-Directional wireless charging system. In particular, in EV using the Inductive Power Transfer(IPT) method, the effective shielding coil position is proposed by analyzing the contribution of the leakage magnetic field of the Ground Assembly(GA) coil and the Vehicle Assembly(VA) coil according to the power transfer direction. Simulations were conducted using the WPT3/Z2 model of the standard SAE J2954, and it was confirmed that the GA coil contributed more to the leakage magnetic field due to the relatively large size compared to the VA coil regardless of power transfer direction.

In the automotive industry, various simulation-based analysis methods have been suggested and applied to reduce the time and cost required to develop the engine structure to improve the NVH performance of powertrain. This simulation is helpful to set the engine design concept in the initial phase of the powertrain development schedules. However, when using the conventional simulation method with a uniformed force, the simulation results sometimes show different results than the test results. Therefore, in this paper, we propose a method for predicting the radiated noise level of a diesel engine using actual combustion excitation force. Based on the analytical radiated noise development target, we identify the major components of the engine that are beyond this development target by in the frequency range. The components of the problem found in this way are reflected in the engine design of the early development stage to shorten the development time.

Knock in gasoline engines at higher loads is a significant constraint on torque and efficiency. The anti-knock property of a fuel is closely related to its research octane number (RON). Ethanol has superior RON compared to gasoline and thus has been commonly used to blend with gasoline in commercial gasolines. However, as the RON of a fuel is constant, it has not been used as needed in a vehicle. To wisely use the RON, an On-Board Separation (OBS) unit that separates commercial gasoline with ethanol content into high-octane fuel with high ethanol fraction and a lower octane remainder has been developed. Then an onboard Octane-on-demand (OOD) concept uses both fuels in varying proportion to provide to the engine a fuel blend with just enough RON to meet the ever changing octane requirement that depends on driving pattern.

The modeling and simulation pyramid in defense states it clearly: Multi-Level modeling and simulation are required. Models and simulations are often classified by the US Department of Defense into four levels—campaign, mission, engagement, and engineering. Campaign simulation models are applied for evaluation; mission-level simulations to experiment with the integration of several macro agents; engagement simulations in engineered systems development; and engineering-level simulation models with a solid foundation in structural physics and components. Models operating at one level must be able to interact with models at another level. Therefore, the cure (“silver bullet”) is very clear: a comprehensive framework for Multiple Resolution Modeling (MRM) is needed. In this paper, we discuss our research about how to construct MRM environments.