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A Lagrangian random vortex-boundary element method has been developed for the simulation of unsteady incompressible flow inside three-dimensional domains with time-dependent boundaries, similar to IC engines. The solution method is entirely grid-free in the fluid domain and eliminates the difficult task of volumetric meshing of the complex engine geometry. Furthermore, due to the Lagrangian evaluation of the convective processes, numerical viscosity is virtually removed; thus permitting the direct simulation of flow at high Reynolds numbers. In this paper, a brief description of the numerical methodology is given, followed by an example of induction flow in an off-centered port-cylinder assembly with a harmonically driven piston and a valve seat situated directly below the port. The predicted flow is shown to resemble the flow visualization results of a laboratory experiment, despite the crude approximation used to represent the geometry.

A novel system for the forming of three dimensional sheet metal parts is described that can form a variety of part shapes without the need for fixed tooling, and given only geometry (CAD) information about the desired part. The central elements of this system are a tooling concept based on a programmable discrete die surface and closed-loop shape control. The former give the process the degrees of freedom to change shape rapidly, and the latter is used to insure that the correct shape is formed with a minimum of forming trials. A 540 kN (60 ton) lab press has been constructed with a 0.3 m (12 in) square pair of discrete tools that can be rapidly re-shaped between forming trials. The shape control system uses measured part shapes to determine a shape error and to correct the tooling shape. This correction is based on a unique “Deformation Transfer Function” approach using a spatial frequency decomposition of the surface.

Vehicle steering control can provide assistance to drivers for lane keeping, automated trajectory following, or more extreme evasive maneuvers. An active torque control steering system is designed using Linear Quadratic Regulator (LQR), and its performance was evaluated using the commercial software CARSIM. The system is developed to maintain a desired trajectory for the vehicle in performing evasive maneuvers to avoid imminent crash scenarios. In order to better understand the behavior of the system with different controllers, a simple bicycle model of the vehicle was developed, and an LQR controller was developed to control vehicle steering torque. The controller uses yaw angle, yaw rate, velocity, and position of the vehicle to generate the required steering torque to follow the desired trajectory. An observer was developed to estimate non-measured parameters. Trajectories are generated to follow a lane change before reaching the obstacle.

A method for detecting drivers' intentions is essential to facilitate operating mode transitions between driver and driver assistance systems. We propose a driver behavior recognition method using Hidden Markov Models (HMMs) to characterize and detect driving maneuvers and place it in the framework of a cognitive model of human behavior. HMM-based steering behavior models for emergency and normal lane changes as well as for lane keeping were developed using a moving base driving simulator. Analysis of these models after training and recognition tests showed that driver behavior modeling and recognition of different types of lane changes is possible using HMMs.

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.

After several decades of human spaceflight, the community of space-faring nations has accumulated a diverse and sometimes harrowing history of toxicological events that have plagued human space endeavors almost from the very beginning. Some lessons have been learned in ground-based test beds and others were discovered the hard way - when human lives were at stake in space. From such lessons one can build a risk-management framework for toxicological events to minimize the probability of a harmful exposure, while recognizing that we cannot predict all possible events. Space toxicologists have learned that relatively harmless compounds can be converted by air revitalization systems into compounds that cause serious harm to the crew.

The adoption of turbine engines for automotive power plants has been hampered by the high cost, high leakage and high wear rate of present designs of ceramic-matrix regenerators. Proposals are made and analyzed here for design directions to achieve substantial improvements in all three areas. These include lower-cost extruded and pressed matrices; and clamping seals coupled with incremental movement of the rotary-regenerator matrix.

In the design of a new space suit it is necessary to have requirements that define what mobility space suit joints should be capable of achieving in both a system and at the component level. NASA elected to divide mobility into its constituent parts -- range of motion (ROM) and torque -- in an effort to develop clean design requirements that limit subject performance bias and are easily verified. Unfortunately, the measurement of mobility can be difficult to obtain. Current technologies, such as the Vicon motion capture system, allow for the relatively easy benchmarking of range of motion (ROM) for a wide array of space suit systems. The ROM evaluations require subjects in the suit to accurately evaluate the ranges humans can achieve in the suit. However, when it comes to torque, there are significant challenges for both benchmarking current performance and writing requirements for future suits.

The ability to make accurate decisions concerning early body-in-white architectures is critical to an automaker since these decisions often have long term cost and weight impacts. We address this need with a methodology which can be used to assist in body architecture decisions using process-based technical cost modeling (TCM) as a filter to evaluate alternate designs. Despite the data limitations of early design concepts, TCM can be used to identify key trends for cost-effectiveness between design variants. A compact body-in-white architecture will be used as a case study to illustrate this technique. The baseline steel structure will be compared to several alternate aluminum intensive structures in the context of production volume.

Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.

This paper presents the results of a study of how people interacted with a production voice-command based interface while driving on public roadways. Tasks included phone contact calling, full address destination entry, and point-of-interest (POI) selection. Baseline driving and driving while engaging in multiple-levels of an auditory-vocal cognitive reference task and manual radio tuning were used as comparison points. Measures included self-reported workload, task performance, physiological arousal, glance behavior, and vehicle control for an analysis sample of 48 participants (gender balanced across ages 21-68). Task analysis and glance measures confirm earlier findings that voice-command interfaces do not always allow the driver to keep their hands on the wheel and eyes on the road, as some assume.

Absorption cooling using a lithium chloride/water heat pump can enable lightweight and effective thermal control for Extravehicular Activity (EVA) suits without venting water to the environment. The key components in the system are an absorber/radiator that rejects heat to space and a flexible evaporation cooling garment that absorbs heat from the crew member, This paper describes progress in the design, development, and testing of the absorber/radiator and evaporation cooling garment. New design concepts and fabrication approaches will significantly reduce the mass of the absorber/radiator. We have also identified materials and demonstrated fabrication approaches for production of a flexible evaporation cooling garment, Data from tests of the system's modular components have validated the design models and allowed predictions of the size and weight of a complete system.

The NASA Shuttle Extravehicular Mobility Unit (EMU) uses a non-regenerable absorbent to remove CO2 from an astronaut's breathing loop. A savings in launch weight, storage volume and life cycle cost may be achieved by incorporating a regenerable CO2 removal system into the EMU. This paper will discuss regenerable CO2 sorbents and their impact on the life support system of an EMU. The systems evaluated will be judged on their technical maturity, impact to the EMU, and impacts to space station and shuttle operation

This paper discusses the Portable Life Support Subsystem (PLSS) packaging design work done by the NASA and Hamilton Sundstrand in support of the 3 future space missions; Lunar, Mars and zero-g. The goal is to seek ways to reduce the weight of PLSS packaging, and at the same time, develop a packaging scheme that would make PLSS technology changes less costly than the current packaging methods. This study builds on the results of NASA's in-house 1998 study, which resulted in the “Flex PLSS” concept. For this study the present EMU schematic (low earth orbit) was used so that the work team could concentrate on the packaging. The Flex PLSS packaging is required to: protect, connect, and hold the PLSS and its components together internally and externally while providing access to PLSS components internally for maintenance and for technology change without extensive redesign impact. The goal of this study was two fold: 1.

Future spacesuits will require thermal insulation protection in low-earth orbit (LEO), in the near-earth neighborhood and in planetary environments. In order to satisfy all future exploration needs and lower production and maintenance costs, a common thermal insulation is desirable that will perform well in all these environments. A highly promising material is a fiber-reinforced aerogel composite insulation currently being developed at the Johnson Space Center. This paper presents an overview of aerogels and their manufacture, a summary of the development of a flexible fiber-based aerogel for NASA by Aspen Aerogels, Inc., and performance data of aerogels relative to flexible commercial insulation. Finally, future plans are presented of how an aerogel-based insulation may be integrated into a spacesuit for ground testing as well as for a flight configuration.

Low volume manufacturing has become increasingly important for the automotive industry. Globalization trends have led automakers and their suppliers to operate in developing regions where minimum efficient scales can not always be achieved. With proper maintenance, standard cast iron stamping tools can be used to produce millions of parts, but require large investments. Thus at high production volumes, the impact of the tooling investment on individual piece costs is minimized. However, at low volumes there is a substantial cost penalty. In light of the trends towards localized manufacturing and relatively low demands in some developing markets, low cost stamping tools are needed. Several alternate tooling technologies exist, each of which require significantly lower initial investments, but suffer from greatly reduced tool lives. However, the use of these technologies at intermediate to high volumes requires multiple tool sets thus eliminating their cost advantage.

The piston skirt is an important contributor of friction in the piston assembly. This paper discusses friction contributions from various aspects of the piston skirt. A brief study of piston skirt patterns is presented, with little gains being made by patterning the piston skirt coating. Next the roughness of the piston skirt coating is analyzed, and results show that reducing piston skirt roughness can have positive effects on friction reduction. Finally, an introductory study into the profile of the piston skirt is presented, with the outcome being that friction reduction is possible by optimizing the skirt profile.

The introduction of new safety critical features using software-intensive systems presents a growing challenge to hazard analysis and requirements development. These systems are rich in feature content and can interact with other vehicle systems in complex ways, making the early development of proper requirements critical. Catching potential problems as early as possible is essential because the cost increases exponentially the longer problems remain undetected. However, in practice these problems are often subtle and can remain undetected until integration, testing, production, or even later, when the cost of fixing them is the highest. In this paper, a new technique is demonstrated to perform a hazard analysis in parallel with system and requirements development. The proposed model-based technique begins during early development when design uncertainty is highest and is refined iteratively as development progresses to drive the requirements and necessary design features.

This paper describes a post-race analysis of team KOMMIT EVT’s electric motorcycle data collected during the 2016 Pikes Peak International Hill Climb (PPIHC). The motorcycle consumed approximately 4 kWh of battery energy with an average and maximum speed of 107 km/h and 149 km/h, respectively. It was the second fastest electric motorcycle with a finishing time of 11:10.480. Data was logged of the motorcycle’s speed, acceleration, motor speed, power, currents, voltages, temperatures, throttle position, GPS position, rider’s heart rate and the ambient environment (air temperature, pressure and humidity). The data was used to understand the following factors that may have prevented a faster time: physical fitness of the rider, thermal limits of the motor and controller, available battery energy and the sprocket ratio between the motor and rear wheel.

A design framework based on the principles of lean manufacturing and axiomatic design was used as a guideline for designing an automotive component manufacturing system. A brief overview of this design decomposition is given to review its structure and usefulness. Examples are examined to demonstrate how this design framework was applied to the design of a gear manufacturing system. These examples demonstrate the impact that low-level design decisions can have on high-level system objectives and the need for a systems-thinking approach in manufacturing system design. Results are presented to show the estimated performance improvements resulting from the new system design.