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PEARLITIC malleable iron crankshafts are being used in the new Pontiac engine as a result of recent developments. This paper discusses the physical properties of pearlitic malleable iron such as elastic modulus, fatigue endurance, and tensile strength. According to the author, definite machining economies result from using pearlitic malleable iron crankshafts.

The National Space Biomedical Research Institute (NSBRI), established in 1997, is a twelve-university consortium dedicated to research that will impact mankind's next exploratory steps. The NSBRI's Education and Public Outreach Program (EPOP), is supporting NASA's education mission to, “Inspire the next generations…as only NASA can,” through a comprehensive Kindergarten through post-doctoral education program. The goals of the EPOP are to: communicate space exploration biology to schools; support undergraduate and graduate space-based courses and degrees; fund postdoctoral fellows to pursue space life sciences research; and engage national and international audiences to promote understanding of how space exploration benefits people on Earth. NSBRI EPOP presents its accomplishments as an educational strategy for supporting science education reform, workforce development, and public outreach.

A driving simulator development project at the Systems Engineering and Technical Process Center (SE/TP) is exploring the role of driving simulation in the vehicle design process. The simulator provides two vehicle mockup testing arenas that support a wide field of view, computer-generated image of the road scene which dynamically responds to driver commands as a function of programmable vehicle model parameters. Two unique aspects of the simulator are the fast 65 ms response time and low incidence rate of simulator induced syndrome (about 5%). Preliminary model validation results and data comparing driver performance in a vehicle vs. the simulator indicate accurate handling response dynamics within the on-center handling region (<0.3g lateral acceleration). Applications have included supporting the development of new steering system concepts, as well as evaluating the usability of vehicle controls and displays.

In order to engineer Squeak & Rattle (S&R) free vehicles it is essential to develop an objective measurement method to compare and correlate with customer satisfaction and subjective S&R assessments. Three methods for exciting S&Rs -type surfaces. Excitation methods evaluated were road tests over S&R surfaces, road simulators, and direct body excitation (DBE). The principle of DBE involves using electromagnetic shakers to induce controlled, road-measured vibration into the body, bypassing the tire patch and suspension. DBE is a promising technology for making objective measurements because it is extremely quiet (test equipment noise does not mask S&Rs), while meeting other project goals. While DBE is limited in exposing S&Rs caused by body twist and suspension noises, advantages include higher frequency energy owing to electro-dynamic shakers, continuous random excitation, lower capital cost, mobility, and safety.

In today's business climate rapid access to, and implementation of, new technology is essential to enhance competitive advantage. In the past, universities have been used for research contracts, but to fully utilize the intellectual resources of education institutions, it is essential to approach these relationships from a new basis: alliance. Alliances permit both parties to become active participants and achieve mutually beneficial goals. This paper will examine the drivers and challenges for industrial -- university alliances from both the industrial and academic perspectives.

NASA has long recognized the advantages of providing improved information interfaces to EVA astronauts and has pursued this goal through a number of development programs over the past decade. None of these activities or parallel efforts in industry and academia has so far resulted in the development of an operational system to replace or augment the current extravehicular mobility unit (EMU) Display and Controls Module (DCM) display and cuff checklist. Recent advances in display, communications, and information processing technologies offer exciting new opportunities for EVA information interfaces that can better serve the needs of a variety of NASA missions. Hamilton Sundstrand Space Systems International (HSSSI) has been collaborating with Simon Fraser University and others on the NASA Haughton Mars Project and with researchers at the Massachusetts Institute of Technology (MIT), Boeing, and Symbol Technologies in investigating these possibilities.

The work presented here builds on the practical and effective spot weld fatigue life prediction method, the structural stress method (SSM), that was developed at Stanford University. Constant amplitude loading tests for various spot weld joint configurations have been conducted and the SSM has been shown to accurately predict fatigue life. In this paper refinements to the structural stress approach are first presented, including a variable amplitude fatigue life prediction method based on the SSM and Palmgren-Miner's rule. A test matrix was designed to study the fatigue behavior of spot welds under tensile shear loading conditions. Constant amplitude tests under different R-ratios were performed first to obtain the necessary material properties. Variable amplitude tests were then performed for specimens containing single and multiple welds.

This paper describes a numerical simulation technique applicable to the FMVSS 214 side impact test through the use of the finite element method (FEM) technology. The paper outlines the development of the side impact dummy (SID), moving deformable barrier (MDB) and the test vehicle FEM models, as well as the development of new advanced constitutive models of materials and algorithms in LS-DYNA3D which are related to the topic. Presented in the paper are some initial simulation problems which were encountered and solved, as well as the correlation of the simulation data to the physical test.

Magnesium alloys are the lightest structural metal and recently attention has been focused on using them for structural automotive components. Fatigue and durability studies are essential in the design of these load-bearing components. In 2006, a large multinational research effort, Magnesium Front End Research & Development (MFERD), was launched involving researchers from Canada, China and the US. The MFERD project is intended to investigate the applicability of Mg alloys as lightweight materials for automotive body structures. The participating institutions in fatigue and durability studies were the University of Waterloo and Ryerson University from Canada, Institute of Metal Research (IMR) from China, and Mississippi State University, Westmorland, General Motors Corporation, Ford Motor Company and Chrysler Group LLC from the United States.

Computer simulation of extravehicular activity (EVA) is increasingly being used in planning and training for EVA. A space suit model is an important, but often overlooked, component of an EVA simulation. Because of the inherent difficulties in collecting angle and torque data for space suit joints in realistic conditions, little data exists on the torques that a space suit’s wearer must provide in order to move in the space suit. A joint angle and torque database was compiled on the Extravehicular Maneuvering Unit (EMU), with a novel measurement technique that used both human test subjects and an instrumented robot. Using data collected in the experiment, a hysteresis modeling technique was used to predict EMU joint torques from joint angular positions. The hysteresis model was then applied to EVA operations by mapping out the reach and work envelopes for the EMU.

From November 1970 through August 1971 an extensive program of static and dynamic air cushion inflation tests utilizing human volunteers was conducted at Holloman Air Force Base, New Mexico, sponsored by the Department of Transportation. Forty-one full cushion deployment static firings were made, with air cushion hardware and seating buck environment designed by General Motors. The static series was followed by 35 dynamic sled firings of human volunteers, beginning at 8.6 g (15.1 mph) and culminating at 21.7 g (31.5 mph). A major objective of both the static and dynamic test series was to identify changes in air-cushion design found necessary to improve its protective capability for human beings. Because of the severity of cushion deployment, one modification was made following the initial static tests: The orifice diameter size of the bag inlet was reduced from 1.0 to 0.6 in to diminish the rapidity of bag inflation. This modification proved effective in the dynamic series.

A search for methods of switching a proposed three beam headlight system led to the evaluation of 41 possible schemes. Human factors criteria reduced the original 41 to three systems which were tested in a laboratory with a broad range of subjects. Recordings of practice trials, learning trials, and the responses to visual cues projected on a screen were analyzed. The same test procedure was also used to compare three alternative ways of switching conventional two beam headlight systems. Summary data is presented for the six systems tested grouped by test subject age, sex, and driving experience. The most pronounced difference observed was in the subjective preference rating among two beam switching systems. All systems tested resulted in remarkably few learning and practice trials. Small differences were recorded among systems in operational response time.

Casting, machining and structural simulations were completed on a V8 engine block made in Compacted Graphite Iron (CGI) for use in a racing application. The casting and machining simulations generated maps of predicted tensile strength and residual stress in the block. These strength and stress maps were exported to a finite element structural model of the machined part. Assembly and operating loads were applied, and stresses due to these loads were determined. High cycle fatigue analysis was completed, and three sets of safety factors were calculated using the following conditions: uniform properties and no residual stress, predicted properties and no residual stress, and predicted properties plus residual stress.

The quest for higher efficiency and performance of automotive vehicles requires application of materials with high strength, stiffness and lower weight in their construction. Particulate-reinforced aluminum-matrix composites are cost-competitive materials, which can meet these requirements. MMCC, Inc. has been optimizing particulate-reinforced alloy systems and developing the Advanced Pressure Infiltration Casting (APIC™) process for the manufacture of components from these materials. This paper discusses the results of a recent study in which composites reinforced with 55 vol.% alumina were cast using two sizes of alumina particulate and eight different matrix alloys based on Al-4.5 wt.% Cu with varying amounts of silicon and magnesium. Optimum heat treatments for each alloy were determined utilizing microhardness studies. The tensile strength and fracture toughness were evaluated as a function of alloy chemistry, particulate size, and heat treatment.

Hybrid powertrains with multiple sources of power have generated new control challenges in the automotive industry. Purdue University's participation in EcoCAR 2, an Advanced Vehicle Technology Competition managed by the Argonne National Laboratories and sponsored by GM and DOE, has provided an exciting opportunity to create a comprehensive test-bench for the development and validation of advanced hybrid powertrain control strategies. As one of 15 competing university teams, the Purdue EcoMakers are re-engineering a donated 2013 Chevrolet Malibu into a plug-in parallel- through-the-road hybrid-electric vehicle, to reduce its environmental impact without compromising performance, safety or consumer acceptability. This paper describes the Purdue team's control development process for the EcoCAR 2 competition.

To manage the function of a vehicle's engine, transmission, and related subsystems, almost all modern vehicles make use of one or more electronic controllers running embedded software, henceforth referred to as a Powertrain Controller System or PCS. Fully validating this PCS is a necessary step of vehicle development, and the validation process requires extensive amounts of testing. Within the automotive industry, more and more of this validation testing is being performed using Hardware-in-the-Loop (HIL) simulators to automate the extensive test sequences. A HIL simulation typically mates the physical PCS to a closed-loop real time computer simulation of a powertrain. Interfacing the physical PCS hardware to a powertrain simulation requires the HIL simulator to have extensive signal input/output (I/O) electronics and simulated actuator electrical loading.

This paper assesses the potential improvement of automotive powertrain technologies 25 years into the future. The powertrain types assessed include naturally-aspirated gasoline engines, turbocharged gasoline engines, diesel engines, gasoline-electric hybrids, and various advanced transmissions. Advancements in aerodynamics, vehicle weight reduction and tire rolling friction are also taken into account. The objective of the comparison is the potential of anticipated improvements in these powertrain technologies for reducing petroleum consumption and greenhouse gas emissions at the same level of performance as current vehicles in the U.S.A. The fuel consumption and performance of future vehicles was estimated using a combination of scaling laws and detailed vehicle simulations. The results indicate that there is significant potential for reduction of fuel consumption for all the powertrains examined.

As component and systems sophistication in both cars and trucks increase, improved diagnostic capabilities are required to assure proper and expedient serviceability. Replacement of electrical modules, starter motors, carburetors, fuel injectors and even whole engines or transmissions is encouraged by high labor costs and continued vehicle mobility mandates. The remanufacturing business has grown and components previously discarded now provide valuable core elements to feed the industry. To achieve efficient utilization of capital, equipment and labor, remanufacturers must estimate when this supply of core elements will be available and plan their production schedules accordingly. In order to properly service private individuals and commercial fleets, minimize vehicle downtime and reduce life cycle costs, adaptation of available analytical tools must be made.

Advances in avionics and display technology are significantly changing the cockpit environment in current transport aircraft. The MIT Aeronautical Systems Lab (ASL) has developed a part-task flight simulator specifically to study the effects of these new technologies on flight crew situational awareness and performance. The simulator is based on a commercially-available graphics workstation, and can be rapidly reconfigured to meet the varying demands of experimental studies. The simulator has been successfully used to evaluate graphical microburst alerting displays, electronic instrument approach plates, terrain awareness and alerting displays, and ATC routing amendment delivery through digital datalinks.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.