Characterization of an embedded RF-MEMS switch

An RF-MEMS capacitive switch for mm-wave integrated circuits, embedded in the BEOL of 0.25μm BiCMOS process, has been characterized. First, a mechanical model based on Finite-Element-Method (FEM) was developed by taking the residual stress of the thin film membrane into account. The pull-in voltage and the capacitance values obtained with the mechanical model agree very well with the measured values. Moreover, S-parameters were extracted using Electromagnetic (EM) solver. The data observed in this way also agree well with the experimental ones measured up to 110GHz. The developed RF model was applied to a transmit/receive (T/R) antenna switch design. The results proved the feasibility of using the FEM model in circuit simulations for the development of RF-MEMS switch embedded, single-chip multi-band RF ICs

A knowledge-based system design/information tool

The objective of this effort was to develop a Knowledge Capture System (KCS) for the Integrated Test Facility (ITF) at the Dryden Flight Research Facility (DFRF). The DFRF is a NASA Ames Research Center (ARC) facility. This system was used to capture the design and implementation information for NASA's high angle-of-attack research vehicle (HARV), a modified F/A-18A. In particular, the KCS was used to capture specific characteristics of the design of the HARV fly-by-wire (FBW) flight control system (FCS). The KCS utilizes artificial intelligence (AI) knowledge-based system (KBS) technology. The KCS enables the user to capture the following characteristics of automated systems: the system design; the hardware (H/W) design and implementation; the software (S/W) design and implementation; and the utilities (electrical and hydraulic) design and implementation. A generic version of the KCS was developed which can be used to capture the design information for any automated system. The deliverable items for this project consist of the prototype generic KCS and an application, which captures selected design characteristics of the HARV FCS

Ship product modelling

This paper is a fundamental review of ship product modeling techniques with a focus on determining the state of the art, to identify any shortcomings and propose future directions. The review addresses ship product data representations, product modeling techniques and integration issues, and life phase issues. The most significant development has been the construction of the ship Standard for the Exchange of Product Data (STEP) application protocols. However, difficulty has been observed with respect to the general uptake of the standards, in particular with the application to legacy systems, often resulting in embellishments to the standards and limiting the ability to further exchange the product data. The EXPRESS modeling language is increasingly being superseded by the extensible mark-up language (XML) as a method to map the STEP data, due to its wider support throughout the information technology industry and its more obvious structure and hierarchy. The associated XML files are, however, larger than those produced using the EXPRESS language and make further demands on the already considerable storage required for the ship product model. Seamless integration between legacy applications appears to be difficult to achieve using the current technologies, which often rely on manual interaction for the translation of files. The paper concludes with a discussion of future directions that aim to either solve or alleviate these issues

Artificial consciousness and the consciousness-attention dissociation

Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to implement sophisticated forms of human intelligence in machines. This research attempts to model specific forms of intelligence through brute-force search heuristics and also reproduce features of human perception and cognition, including emotions. Such goals have implications for artificial consciousness, with some arguing that it will be achievable once we overcome short-term engineering challenges. We believe, however, that phenomenal consciousness cannot be implemented in machines. This becomes clear when considering emotions and examining the dissociation between consciousness and attention in humans. While we may be able to program ethical behavior based on rules and machine learning, we will never be able to reproduce emotions or empathy by programming such control systems—these will be merely simulations. Arguments in favor of this claim include considerations about evolution, the neuropsychological aspects of emotions, and the dissociation between attention and consciousness found in humans. Ultimately, we are far from achieving artificial consciousness

Capturing design process information and rationale to support knowledge-based design and analysis integration

Issued as final reportUnited States. Dept. of Commerc

On the role of domain ontologies in the design of domain-specific visual modeling langages

Domain-Specific Visual Modeling Languages should provide notations and abstractions that suitably support problem solving in well-defined application domains. From their user’s perspective, the language’s modeling primitives must be intuitive and expressive enough in capturing all intended aspects of domain conceptualizations. Over the years formal and explicit representations of domain conceptualizations have been developed as domain ontologies. In this paper, we show how the design of these languages can benefit from conceptual tools developed by the ontology engineering community

Modeling the Structure and Complexity of Engineering Routine Design Problems

This paper proposes a model to structure routine design problems as well as a model of its design complexity. The idea is that having a proper model of the structure of such problems enables understanding its complexity, and likewise, a proper understanding of its complexity enables the development of systematic approaches to solve them. The end goal is to develop computer systems capable of taking over routine design tasks based on generic and systematic solving approaches. It is proposed to structure routine design in three main states: problem class, problem instance, and problem solution. Design complexity is related to the degree of uncertainty in knowing how to move a design problem from one state to another. Axiomatic Design Theory is used as reference for understanding complexity in routine design

Quantifying Changes in Creativity: Findings from an Engineering Course on the Design of Complex and Origami Structures

Engineering educators have increasingly sought strategies for integrating the arts into their curricula. The primary objective of this integration varies, but one common objective is to improve students’ creative thinking skills. In this paper, we sought to quantify changes in student creativity that resulted from participation in a mechanical engineering course targeted at integrating engineering, technology, and the arts. The course was team taught by instructors from mechanical engineering and art. The art instructor introduced origami principles and techniques as a means for students to optimize engineering structures. Through a course project, engineering student teams interacted with art students to perform structural analysis on an origami-based art installation, which was the capstone project of the art instructor’s undergraduate origami course. Three engineering student teams extended this course project to collaborate with the art students in the final design and physical installation. To evaluate changes in student creativity, we used two instruments: a revised version of the Reisman Diagnostic Creativity Assessment (RDCA) and the Innovative Behavior Scales. Initially, the survey contained 12 constructs, but three were removed due to poor internal consistency reliability: Extrinsic Motivation; Intrinsic Motivation; and Tolerance of Ambiguity. The nine remaining constructs used for comparison herein included: • Originality: Confidence in developing original, innovative ideas • Ideation: Confidence in generating many ideas • Risk Taking: Adventurous; Brave • Openness of Process: Engaging various potentialities and resisting closure • Iterative Processing: Willingness to iterate on one’s solution • Questioning: Tendency to ask lots of questions • Experimenting/exploring: Tendency to physically or mentally take things apart • Idea networking: Tendency to engage with diverse others in communicative acts • Observing: Tendency to observe the surrounding world By conducting a series of paired t-tests to ascertain if pre and post-course responses were significantly different on the above constructs, we found five significant changes. In order of significance, these included Idea Networking; Questioning; Observing; Originality; and Ideation. To help explain these findings, and to identify how this course may be improved in subsequent offerings, the discussion includes the triangulation of these findings in light of teaching observations, responses from a mid-semester student focus group session, and informal faculty reflections. We close with questions that we and others ought to address as we strive to integrate engineering, technology, and the arts. We hope that these findings and discussion will guide other scholars and instructors as they explore the impact of art on engineering design learning, and as they seek to evaluate student creativity resulting from courses with similar aims