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In order to sustain in automobile industry, fuel economy and robustness are playing vital role in vehicle. Every gram of weight will have an impact on fuel economy, thus burning a hole in consumers pocket and contributing heavily to the carbon footprint. Composite material development plays important role in meeting the stringent self-imposed targets of the automotive manufacturers and light weighting is becoming a prime option for improving Fuel Economy. The main objective of this paper is to optimize the weight of the luggage lid floor and reduce its cost without compromising on the strength by changing the raw material and manufacturing process. This part is in trunk compartment of the vehicle. Main function of this part is to withstand the luggage load under various user loading patterns at varied temperature and while driving on different road conditions.

In this study, the role of turbulence-chemistry interaction in diesel spray auto-ignition, flame stabilization and end of injection phenomena is investigated under engine relevant “Spray A” conditions. A recently developed diesel spray combustion modeling approach, Conditional Source-term Estimation (CSE-FGM), is coupled with Reynolds-averaged Navier-Stokes simulation (RANS) framework to study the details of spray combustion. The detailed chemistry mechanism is included through the Flamelet Generated Manifold (FGM) method. Both unsteady and steady flamelet solutions are included in the manifold to account for the auto-ignition process and the subsequent flame propagation in a diesel spray. Conditionally averaged chemical source terms are closed by the conditional scalars obtained in the CSE routine. Both non-reacting and reacting spray jets are computed over a wide range of Engine Combustion Network (ECN) diesel. “Spray A” conditions. The reacting spray results are compared with simulations using a homogeneous reactor combustion model and a flamelet combustion model with the same chemical mechanism. The present study represents the first application of CSE for a diesel spray. The non-reacting liquid/vapour penetration, the mean and RMS mixture fraction, the reactive region, the flame lift-off and the ignition delay show a good agreement with literature data from an optically accessible combustion vessel over a wide range of tested conditions. The CSE-FGM model also shows a better capability in predicting the end-of-injection events in diesel spray combustion. Overall, the CSE-FGM model is shown to capture the experimental trends well, both quantitatively and qualitatively.

Stress, fatigue, and workload affect worker performance. NSF reported that 61% of respondents state losing concentration at work while 79% occasionally or frequently made errors as a result of being fatigued. Shift work, altered work schedules, long hours of continuous wakefulness, and sleep loss can create sleep and circadian disruptions that degrade waking fundions causing stress and fatigue. Review of the literature has proven void of information that links the combined effects of fatigue, stress, and workload to human performance. This paper will address which occupational factors within stress, fatigue, and workload were identified as occupational contributors to performance changes. The results of this research will be apglied to underlying models and algorithms that will help predict performance changes in control room operators.

Automated solutions for manufacturing composite products based on prepreg often imply Automatic Fiber Placement or Automatic Tape Laying. These systems are generally associated with huge investments. For certain manufacturing applications it is interesting to investigate alternatives to find simpler and less costly automation. One example of an automated system could be the use of a standard industrial robot to pick single prepreg plies from an automated cutting machine and stack them to form a plane laminate. This paper is based on a case illustrating a product from the aircraft manufacturing industry. The case will demonstrate a pick and place concept on a general level and illustrate challenges that must be solved. The challenge selected to be the main focus for this paper is an automated process for backing paper removal. A literature review of different gripping technologies reveals several interesting technologies, and the most promising are tested for backing paper removal. The tests show that an automated removal process can be designed by using standard vacuum grippers in combination with mechanical clamping grippers. In order to lift the backing paper with a vacuum gripper an initial separation between the backing paper and prepreg is needed. This separation is most easily mechanically induced by bending the material. The proposed solution for automatic backing paper removal can be integrated in a manufacturing cell for manufacturing of the studied product. SAE Technical Paper 2013-01-2289

The Advanced Extra-vehicular Activity (EVA) team of the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC) Crew and Thermal Systems Division (CTSD) participated in the Desert Research and Technology Study (RATS) in September 2003, at Meteor Crater, AZ. The Desert RATS is an integrated remote field site te t with team members from several NASA centers (Johnson Space Center; Glenn and Ames Research Centers) and universities (Bowling Green State University, University of Cincinnati, Massachusetts Institute of Technology) participating. Each week of the two-week field test had a primary focus. The primary test hardware for the first week was the I-Gravity Lunar Rover Training Vehicle, or Grover, which was on loan to NASA from the United States Geological Survey (USGS) Astrogeology Research Program. The 2003 Grover driving test results serve as a rover performance characterization baseline for the Science, Crew, Operation and Utility Testbed (SCOUT) project team, which will be designing and fabricating a next generation roving vehicle prototype in Fiscal Year (FY) 2004. The second week of testing focused on EVA geologic traverses that utilized a geologic sample field analysis science trailer and also focused on human-robotic interaction between the suited subjects and the EVA Robotic Assistant (ERA). This paper will review the Advanced EVA team's role in the context of the overall Desert RATS, as well as the EVA team results and lessons learned. For information regarding other test participants' results, the authors can refer interested parties to the test reports produced by those Desert RATS teams.