The Stanford how things work project

We provide an overview of the Stanford How Things Work (HTW) project, an ongoing integrated collection of research activities in the Knowledge Systems Laboratory at Stanford University. The project is developing technology for representing knowledge about engineered devices in a form that enables the knowledge to be used in multiple systems for multiple reasoning tasks and reasoning methods that enable the represented knowledge to be effectively applied to the performance of the core engineering task of simulating and analyzing device behavior. The central new capabilities currently being developed in the project are automated assistance with model formulation and with verification that a design for an electro-mechanical device satisfies its functional specification

Operator procedure verification with a rapidly reconfigurable simulator

Generating and testing procedures for controlling spacecraft subsystems composed of electro-mechanical and computationally realized elements has become a very difficult task. Before a spacecraft can be flown, mission controllers must envision a great variety of situations the flight crew may encounter during a mission and carefully construct procedures for operating the spacecraft in each possible situation. If, despite extensive pre-compilation of control procedures, an unforeseen situation arises during a mission, the mission controller must generate a new procedure for the flight crew in a limited amount of time. In such situations, the mission controller cannot systematically consider and test alternative procedures against models of the system being controlled, because the available simulator is too large and complex to reconfigure, run, and analyze quickly. A rapidly reconfigurable simulation environment that can execute a control procedure and show its effects on system behavior would greatly facilitate generation and testing of control procedures both before and during a mission. The How Things Work project at Stanford University has developed a system called DME (Device Modeling Environment) for modeling and simulating the behavior of electromechanical devices. DME was designed to facilitate model formulation and behavior simulation of device behavior including both continuous and discrete phenomena. We are currently extending DME for use in testing operator procedures, and we have built a knowledge base for modeling the Reaction Control System (RCS) of the space shuttle as a testbed. We believe that DME can facilitate design of operator procedures by providing mission controllers with a simulation environment that meets all these requirements

Stretched Lens Array (SLA) for Collection and Conversion of Infrared Laser Light: 45% Efficiency Demonstrated for Near-Term 800 W/kg Space Power System

For the past 2% years, our team has been developing a unique photovoltaic concentrator array for collection and conversion of infrared laser light. This laser-receiving array has evolved from the solar-receiving Stretched Lens Array (SLA). The laser-receiving version of SLA is being developed for space power applications when or where sunlight is not available (e.g., the eternally dark lunar polar craters). The laser-receiving SLA can efficiently collect and convert beamed laser power from orbiting spacecraft or other sources (e.g., solar-powered lasers on the permanently illuminated ridges of lunar polar craters). A dual-use version of SLA can produce power from sunlight during sunlit portions of the mission, and from beamed laser light during dark portions of the mission. SLA minimizes the cost and mass of photovoltaic cells by using gossamer-like Fresnel lenses to capture and focus incoming light (solar or laser) by a factor of 8.5X, thereby providing a cost-effective, ultra-light space power system

Comparison of Autoclave and Out-of-Autoclave Composites

The National Aeronautics and Space Administration (NASA) Exploration Systems Mission Directorate initiated an Advanced Composite Technology Project through the Exploration Technology Development Program in order to support the polymer composite needs for future heavy lift launch architectures. As an example, the large composite dry structural applications on Ares V inspired the evaluation of autoclave and out-of-autoclave (OOA) composite materials. A NASA and industry team selected the most appropriate materials based on component requirements for a heavy lift launch vehicle. Autoclaved and OOA composites were fabricated and results will highlight differences in processing conditions, laminate quality, as well as initial room temperature thermal and mechanical performance. Results from this study compare solid laminates that were both fiber-placed and hand-laid. Due to the large size of heavy-lift launch vehicle composite structures, there is significant potential that the uncured composite material or prepreg will experience significant out-life during component fabrication. Therefore, prepreg out-life was a critical factor examined in this comparison. In order to rigorously test material suppliers recommended out-life, the NASA/Industry team extended the out-time of the uncured composite prepreg to values that were approximately 50% beyond the manufacturers out-time limits. Early results indicate that the OOA prepreg composite materials suffered in both composite quality and mechanical property performance from their extended out-time. However, the OOA materials performed similarly to the autoclaved composites when processed within a few days of exposure to ambient "shop" floor handling. Follow on studies evaluating autoclave and OOA aluminum honeycomb core sandwich composites are planned

Predicting the Effect of Surface Texture on the Qualitative Form of Prehension

Reach-to-grasp movements change quantitatively in a lawful (i.e. predictable) manner with changes in object properties. We explored whether altering object texture would produce qualitative changes in the form of the precontact movement patterns. Twelve participants reached to lift objects from a tabletop. Nine objects were produced, each with one of three grip surface textures (high-friction, medium-friction and low-friction) and one of three widths (50 mm, 70 mm and 90 mm). Each object was placed at three distances (100 mm, 300 mm and 500 mm), representing a total of 27 trial conditions. We observed two distinct movement patterns across all trials—participants either: (i) brought their arm to a stop, secured the object and lifted it from the tabletop; or (ii) grasped the object ‘on-the-fly’, so it was secured in the hand while the arm was moving. A majority of grasps were on-the-fly when the texture was high-friction and none when the object was low-friction, with medium-friction producing an intermediate proportion. Previous research has shown that the probability of on-the-fly behaviour is a function of grasp surface accuracy constraints. A finger friction rig was used to calculate the coefficients of friction for the objects and these calculations showed that the area available for a stable grasp (the ‘functional grasp surface size’) increased with surface friction coefficient. Thus, knowledge of functional grasp surface size is required to predict the probability of observing a given qualitative form of grasping in human prehensile behaviour

Developing manufacturing control software: A survey and critique

The complexity and diversity of manufacturing software and the need to adapt this software to the frequent changes in the production requirements necessitate the use of a systematic approach to developing this software. The software life-cycle model (Royce, 1970) that consists of specifying the requirements of a software system, designing, implementing, testing, and evolving this software can be followed when developing large portions of manufacturing software. However, the presence of hardware devices in these systems and the high costs of acquiring and operating hardware devices further complicate the manufacturing software development process and require that the functionality of this software be extended to incorporate simulation and prototyping.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45542/1/10696_2005_Article_BF01328739.pd

FORMALIZING ELABORATION TOLERANCE

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Environmental Monitoring for Situation Assessment using Mobile and Fixed Sensors

This project was co-led by Dr. Sheila McIlraith and Prof. Richard Fikes. Substantial research results and published papers describing those results were produced in multiple technology areas, including the following: 1) Monitoring a Complex Physical System using a Hybrid Dynamic Bayes Net; 2) A Formal Theory of Testing for Dynamical Systems; 3) Diagnosing Hybrid Systems Using a Bayesian Model Selection Approach