Neural network fitness functions for a musical IGA

This paper describes recent enhancements to GenJam, a genetic algorithm-based model of a novice jazz musician learning to improvise. After presenting an overview and update of the current interactive version of GenJam, we focus on efforts to augment its human fitness function with a neural network, in an attempt to ease the fitness bottleneck inherent in musical IGAs. Specifically, a cascade correlation technique was used with data taken from populations of musical ideas trained by human mentors interactively. We conclude with a discussion of why this approach failed, and we speculate on approaches that might work

Effectiveness of Shot Peening In Suppressing Fatigue Cracking At Non-Metallic Inclusions In Udimet(Registered Trademark)720

The fatigue lives of modern powder metallurgy disk alloys can be reduced over an order of magnitude by cracking at inherent non-metallic inclusions. The objective of this work was to study the effectiveness of shot peening in suppressing LCF crack initiation and growth at surface nonmetallic inclusions. Inclusions were carefully introduced at elevated levels during powder metallurgy processing of the nickel-base disk superalloy Udimet 720. Multiple strain-controlled fatigue tests were then performed on machined specimens with and without shot peened test sections at 427 C and 650 C. The low cycle fatigue lives and failure initiation sites varied as functions of inclusion content, shot peening, and fatigue conditions. A large majority of the failures in as-machined specimens with the introduced inclusions occurred at cracks initiating from inclusions intersecting the specimen surface. These inclusions reduced fatigue life by up to 100X, when compared to lives of material without inclusions residing at specimen surface. Large inclusions produced the greatest reductions in life for tests at low strain ranges and high strain ratios. Shot peening improved life in many cases by reducing the most severe effects of inclusions

Computational steering of a multi-objective evolutionary algorithm for engineering design

The execution process of an evolutionary algorithm typically involves some trial and error. This is due to the difficulty in setting the initial parameters of the algorithm—especially when little is known about the problem domain. This problem is magnified when applied to many-objective optimisation, as care is needed to ensure that the final population of candidate solutions is representative of the trade-off surface. We propose a computational steering system that allows the engineer to interact with the optimisation routine during execution. This interaction can be as simple as monitoring the values of some parameters during the execution process, or could involve altering those parameters to influence the quality of the solutions produced by the optimisation process. The implementation of this steering system should provide the ability to tailor the client to the hardware available, for example providing a lightweight steering and visualisation client for use on a PDA

Evaluation of Musical Creativity and Musical Metacreation Systems

The field of computational creativity, including musical metacreation, strives to develop artificial systems that are capable of demonstrating creative behavior or producing creative artefacts. But the claim of creativity is often assessed, subjectively only on the part of the researcher and not objectively at all. This article provides theoretical motivation for more systematic evaluation of musical metacreation and computationally creative systems and presents an overview of current methods used to assess human and machine creativity that may be adapted for this purpose. In order to highlight the need for a varied set of evaluation tools, a distinction is drawn among three types of creative systems: those that are purely generative, those that contain internal or external feedback, and those that are capable of reflection and self-reflection. To address the evaluation of each of these aspects, concrete examples of methods and techniques are suggested to help researchers (1) evaluate their systems' creative process and generated artefacts, and test their impact on the perceptual, cognitive, and affective states of the audience, and (2) build mechanisms for reflection into the creative system, including models of human perception and cognition, to endow creative systems with internal evaluative mechanisms to drive self-reflective processes. The first type of evaluation can be considered external to the creative system and may be employed by the researcher to both better understand the efficacy of their system and its impact and to incorporate feedback into the system. Here we take the stance that understanding human creativity can lend insight to computational approaches, and knowledge of how humans perceive creative systems and their output can be incorporated into artificial agents as feedback to provide a sense of how a creation will impact the audience. The second type centers around internal evaluation, in which the system is able to reason about its own behavior and generated output. We argue that creative behavior cannot occur without feedback and reflection by the creative/metacreative system itself. More rigorous empirical testing will allow computational and metacreative systems to become more creative by definition and can be used to demonstrate the impact and novelty of particular approaches

Knight Cancer Research Building

The Knight Cancer Research Building (KCRB) will be a 7-story research facility with a proposed site in the South Waterfront district. It will be the first building of a two-phase construction project; the second building, expected for completion in about 10 years, will connect to the KCRB\u27s north facade. Until then, the KCRB north facade will be visually and environmentally exposed. The north facade will include an atrium flanked by more enclosed spaces such as egress stairs, storage, and meeting rooms. The south facade of the Phase II building will define the remaining walls of the atrium as its lower levels will nearly mirror KCRB\u27s north fa9ade. The north facade atrium design began as all-glass and spanned several levels in order to create a desirable communal space for the occupants. The engineering consultants for the project had expressed concern about the thermal performance of an all-glass design and recommended that the north facade have some mass to decrease solar gain in the summer and heat loss in the winter. The first half of this research project focused on exploring design alternatives and their impact on thermal performance and daylighting. Before the completion of this study, a final fa9ade design was chosen by SRG, so there was a change in direction for the second half of the research project. SRG wanted to better understand how a cut-out feature on the Phase II building might influence atrium daylighting and asked that a study be conducted.https://pdxscholar.library.pdx.edu/research_based_design/1058/thumbnail.jp

Training Neural Networks Using a Genetic Algorithm and an Iterated Pseudo-Inverse

We present a rapid training algorithm for two-layer, feed-forward neural networks. The first layer of weights is determined by a genetic algorithm, the second layer by an iterated pseudo-inverse. We apply our method to problems such as parity and encoder-decoder (the latter is of the form "N --M --N ," with M ! N , in which the input and output of the net are identical). The network's form is: y = oe 1 Vx followed by z = oe 2 Wy, where x, y, and z are the input, hidden, and output vectors; V and W are the weights matrices; oe 1 is a piecewise linear function, and oe 2 is sign. A genetic algorithm evolves V using a fitness function based on the network 's performance after W has been determined by an iterated pseudoinverse. Feed-Forward Networks We study feed-forward neural networks with two layers of weights; i.e., systems, denoted by N --M --K, consisting of an input vector x with N entries, a hidden vector y with M real entries, and an output vector z with K entries. The entries o..

Effectiveness of Shot Peening in Suppressing Fatigue Cracking at Non-Metallic Inclusions in Udimet(trademark) 720

The fatigue lives of modern powder metallurgy disk alloys can be reduced by over an order of magnitude by surface cracking at inherent non-metallic inclusions. The objective of this work was to study the effectiveness of shot peening in suppressing LCF crack initiation and growth at surface nonmetallic inclusions. Inclusions were carefully introduced at elevated levels during powder metallurgy processing of the nickel-base disk superalloy Udimet 720. Multiple strain-controlled fatigue tests were then performed on machined specimens at 427 and 650 C in peened and unpeened conditions. Analyses were performed to compare the low cycle fatigue lives and failure initiation sites as a function of inclusion content, shot peening, and fatigue conditions. A large majority of the failures in as-machined specimens with introduced inclusions occurred at cracks initiating from inclusions intersecting the specimen surface. The inclusions could reduce fatigue life by up to 100X. Large inclusions had the greatest effect on life in tests at low strain ranges and high strain ratios. Shot peening can be used to improve life in these conditions by reducing the most severe effects of inclusions