Thesis (Ed. D.)--Lehigh University, 2006. / Includes vita. Includes bibliographical references (leaves 84-96).

Efficiency and innovative problem solving are contradictory requirements for productdevelopment (PD), and both requirements must be satisfied in companies that strive to remainor to become competitive. Efficiency is strongly related to ”doing things right”, whereasinnovative problem solving and creativity is focused on ”doing the right things”.Engineering design, which is a sub-process within PD, can be viewed as problem solving or adecision-making process. New technologies in computer science and new software tools openthe way to new approaches for the solution of mechanical problems. Product datamanagement (PDM) technology and tools can enable concurrent engineering (CE) bymanaging the formal product data, the relations between the individual data objects, and theirrelation to the PD process. Many engineering activities deal with the relation betweenbehavior and shape. Modern CAD systems are highly productive tools for conceptembodiment and detailing. The finite element (FE) method is a general tool used to study thephysical behavior of objects with arbitrary shapes. Since a modern CAD technology enablesdesign modification and change, it can support the innovative dimension of engineering aswell as the verification of physical properties and behavior. Concepts and detailed solutionshave traditionally been evaluated and verified with physical testing. Numerical modeling andsimulation is in many cases a far more time efficient method than testing to verify theproperties of an artifact. Numerical modeling can also support the innovative dimension ofproblem solving by enabling parameter studies and observations of real and syntheticbehavior. Simulation-driven design is defined as a design process where decisions related tothe behavior and performance of the artifact are significantly supported by computer-basedproduct modeling and simulation.A framework for product modeling, that is based on a modern CAD system with fullyintegrated FE modeling and simulation functionality provides the engineer with tools capableof supporting a number of engineering steps in all life-cycle phases of a product. Such aconceptual framework, that is based on a moderately coupled approach to integratecommercial PDM, CAD, and FE software, is presented. An object model and a supportingmodular modeling methodology are also presented. Two industrial cases are used to illustratethe possibilities and some of the opportunities given by simulation-driven design with thepresented methodology and framework. / QC 20100810

Background: The term physical behavior includes sedentary and non-sedentary everyday physical activities. Objective measurement methods are recommended when sedentary behaviors are to be measured. Data from a thigh worn accelerometer can, together with the Acti4 software, be used to distinguish different physical behaviors. Due to different shapes of thighs and how the accelerometers have been placed on the thighs there is a need to compensate for individual differences in reference angles in respect to gravity. Normally this is done by letting the participants perform a reference position when they stand up and that time is noted in a diary. However, this is very time  consuming. One alternative is to automatically estimate the compensation angles from walking episodes in the existing data. Objective: The aim of this study was to validate two new features to the Acti4 software, detection of lying and automatic reference angle generation. Methods: Ten participants underwent a 45-minute standardized protocol, and a 48-hour free-living protocol, with recordings of the different physical behaviors lying, sitting, standing, walking, running, stair walking, and cycling. Video recordings of the standardized protocol, and accelerometer data and diaries together with the participants review of the results from the software from the free-living protocol, has been used to validate the software. Results: During the standardized protocol, the overall accumulated performance of the software to identify the same physical behavior as in the video recordings was 81.1% (sensitivity), 96.7% (specificity) and 94.8% (accuracy). Participants agreed that most identified physical behavior episodes were correct, when reviewing the result from the software. When the two different reference angle generation methods were compared, almost no difference was found in the results of the standardized protocol, neither when comparing total time registered per behavior accumulated for all participants during the free-living protocol. Conclusions: The software may be used in research as a valid tool to measure physical behavior. However, the sensitivity to detect lying and stair walking may vary between individuals. When conducting research with thigh worn accelerometers, researchers may use the easier to use method with automatically generated reference angles instead of the more burdensome method with manually recorded diary annotation.