INTERNET CONTENT POLICY AND REGULATION IN AUSTRALIA

It can generally be observed that the propensity for creating new internet content regulation within a country results from the interaction of three forces. Firstly, there are the cultural values and institutions within a country. ‘Institutions’ include the traditional media who have historically acted as drivers of the debate about the harms of being online. Sometimes they are more sensationalist than is justified. In any event, these values and institutions shape the political debate and determine the enthusiasm with which legislatures bring forth new laws, in response, as it were, to public concern. In Australia, the traditional media have been very active in pointing out the ‘dangers’ of the internet. To a large degree they have played on the fears of a public which is still coming to terms with the internet revolution. Although the number of Australians online has progressively grown over the last 10 years, from a minority of mainly young, affluent early adopters, to today where the internet is effectively a mainstream medium with almost three quarters of the population online,1 still the depth of user experience remains thin enough that we see the occasional headline proclaiming the menace of some new internet threat or other. This is enough to fuel minority groups with their own agendas, to proclaim the internet a risk to traditional values/our children’s safety/national security/the future of their business model or whatever cause suits them. This may play all the way through to the political level where we eventually see new laws proposed. This dynamic is certainly not unique to Australia, but we have nevertheless seen the mechanism operate here with sometimes startling results

Deterministic Design Optimization of Structures in OpenMDAO Framework

Nonlinear programming algorithms play an important role in structural design optimization. Several such algorithms have been implemented in OpenMDAO framework developed at NASA Glenn Research Center (GRC). OpenMDAO is an open source engineering analysis framework, written in Python, for analyzing and solving Multi-Disciplinary Analysis and Optimization (MDAO) problems. It provides a number of solvers and optimizers, referred to as components and drivers, which users can leverage to build new tools and processes quickly and efficiently. Users may download, use, modify, and distribute the OpenMDAO software at no cost. This paper summarizes the process involved in analyzing and optimizing structural components by utilizing the framework s structural solvers and several gradient based optimizers along with a multi-objective genetic algorithm. For comparison purposes, the same structural components were analyzed and optimized using CometBoards, a NASA GRC developed code. The reliability and efficiency of the OpenMDAO framework was compared and reported in this report

Simulation of Foam Divot Weight on External Tank Utilizing Least Squares and Neural Network Methods

Simulation of divot weight in the insulating foam, associated with the external tank of the U.S. space shuttle, has been evaluated using least squares and neural network concepts. The simulation required models based on fundamental considerations that can be used to predict under what conditions voids form, the size of the voids, and subsequent divot ejection mechanisms. The quadratic neural networks were found to be satisfactory for the simulation of foam divot weight in various tests associated with the external tank. Both linear least squares method and the nonlinear neural network predicted identical results

Probabilistic Simulation for Nanocomposite Characterization

A unique probabilistic theory is described to predict the properties of nanocomposites. The simulation is based on composite micromechanics with progressive substructuring down to a nanoscale slice of a nanofiber where all the governing equations are formulated. These equations have been programmed in a computer code. That computer code is used to simulate uniaxial strengths properties of a mononanofiber laminate. The results are presented graphically and discussed with respect to their practical significance. These results show smooth distributions

The development and application of autonomous, low-cost, 3D printers

Low-cost 3D printers have empowered individuals to create customized printed parts, but they have yet to be as user friendly as a vending machine. The purpose of this research project is to develop an autonomous, low-cost, 3D printing Vending Machine that would increase access to this technology. This research with 15 students is divided into two teams. One team is responsible for the design concepts required of an additive manufacturing vending machine and the other team is responsible for printing and prototyping the parts using a low-cost 3D printer. The teams have produced printed objects from original designs using kits they built, implemented basic communications, developed design concepts for the vending machine and training strategies to increase access. This multi-disciplinary research provides educational opportunities for students to pursue their interests in the emerging field of additive manufacturing emerging field of additive manufacturing and it addresses critical challenges in wide-spread implementation of this technology across campus

Statistical Analyses of Raw Material Data for MTM45-1/CF7442A-36% RW: CMH Cure Cycle

This report describes statistical characterization of physical properties of the composite material system MTM45-1/CF7442A, which has been tested and is currently being considered for use on spacecraft structures. This composite system is made of 6K plain weave graphite fibers in a highly toughened resin system. This report summarizes the distribution types and statistical details of the tests and the conditions for the experimental data generated. These distributions will be used in multivariate regression analyses to help determine material and design allowables for similar material systems and to establish a procedure for other material systems. Additionally, these distributions will be used in future probabilistic analyses of spacecraft structures. The specific properties that are characterized are the ultimate strength, modulus, and Poissons ratio by using a commercially available statistical package. Results are displayed using graphical and semigraphical methods and are included in the accompanying appendixes

Reliability-Based Design Optimization of a Composite Airframe Component

A stochastic optimization methodology (SDO) has been developed to design airframe structural components made of metallic and composite materials. The design method accommodates uncertainties in load, strength, and material properties that are defined by distribution functions with mean values and standard deviations. A response parameter, like a failure mode, has become a function of reliability. The primitive variables like thermomechanical loads, material properties, and failure theories, as well as variables like depth of beam or thickness of a membrane, are considered random parameters with specified distribution functions defined by mean values and standard deviations

Structural Analysis and Optimization of a Composite Fan Blade for Future Aircraft Engine

This report addresses the structural analysis and optimization of a composite fan blade sized for a large aircraft engine. An existing baseline solid metallic fan blade was used as a starting point to develop a hybrid honeycomb sandwich construction with a polymer matrix composite face sheet and honeycomb aluminum core replacing the original baseline solid metallic fan model made of titanium. The focus of this work is to design the sandwich composite blade with the optimum number of plies for the face sheet that will withstand the combined pressure and centrifugal loads while the constraints are satisfied and the baseline aerodynamic and geometric parameters are maintained. To satisfy the requirements, a sandwich construction for the blade is proposed with composite face sheets and a weak core made of honeycomb aluminum material. For aerodynamic considerations, the thickness of the core is optimized whereas the overall blade thickness is held fixed so as to not alter the original airfoil geometry. Weight is taken as the objective function to be minimized by varying the core thickness of the blade within specified upper and lower bounds. Constraints are imposed on radial displacement limitations and ply failure strength. From the optimum design, the minimum number of plies, which will not fail, is back-calculated. The ply lay-up of the blade is adjusted from the calculated number of plies and final structural analysis is performed. Analyses were carried out by utilizing the OpenMDAO Framework, developed at NASA Glenn Research Center combining optimization with structural assessment