Simulation on the process of fatigue crack initiation in a martensitic stainless steel

Die vorliegende Arbeit beschäftigt sich mit der Computersimulation des Rissinitiierungsprozesses für einen martensitischen Stahl, der der niederzyklischen Ermüdung unterworfen wurde. Wie auf der Probenoberfläche beobachtet wurde, sind die Initiierung und das frühe Wachstum dieser Mikrorisse in hohem Grade von der Mikrostruktur abhängig. Diese Tatsache wurde in mesoskopischen Schädigungsmodellen beschrieben, wobei die Körner als einzelne Kristalle mit anisotropem Materialverhalten modelliert wurden. Das repräsentative Volumenelement (RVE), das durch einen Voronoi-Zerlegung erzeugt wurde, wurde benutzt, um die Mikrostruktur des polykristallinen Materials zu simulieren. Spannungsverteilungen wurden mit Hilfe der Finiten-Elemente-Methode mit elastischen und elastoplastischen Materialeigenschaften analysiert. Dazu wurde die Simulation zunächst an zweidimensionalen Modellen durchgeführt. Ferner wurde ein vereinfachtes dreidimensionales RVE hinsichtlich des sowohl dreidimensionalen Gleitsystems als auch Spannungszustandes verwendet. Die kontinuierliche Rissinitiierung wurde simuliert, indem der Risspfad innerhalb jedes Kornes definiert wurde. Die Zyklenanzahl bis zur Rissinitiierung wurde auf Grundlage der Tanaka-Mura- und Chan-Gleichungen ermittelt. Die Simulation lässt auf die Flächendichten der einsegmentige Risse in Relation zur Zyklenanzahl schließen. Die Resultate wurden mit experimentellen Daten verglichen. Für alle Belastungsdehnungen sind die Simulationsergebnisse mit denen der experimentellen Daten vergleichbar.

Applicability of Emergence Engineering to Distributed Systems Scenarios

Genetic Programming can be effectively used to create emergent behavior for a group of autonomous agents. In the process we call Offline Emergence Engineering, the behavior is at first bred in a Genetic Programming environment and then deployed to the agents in the real environment. In this article we shortly describe our approach, introduce an extended behavioral rule syntax, and discuss the impact of the expressiveness of the behavioral description to the generation success, using two scenarios in comparison: the election problem and the distributed critical section problem. We evaluate the results, formulating criteria for the applicability of our approach.

An Experimental Multimedia Process Control Room

The centralised control rooms of large industrial plants have separated people from the processes they should control. Perception is restricted mainly to the visual sense. Only telephone or radio links provide narrow-band voice communication with maintenance personnel down in the plant. Multimedia equipment can perceptionally bring back the operator into the plant while bodily keeping him the comfortable and safe control room. This involves video and audio transmission from process components as well as sights and sounds artificially generated from measurements. Groupware systems support inter-action between operators, engineers, and managers in different plants. With support from the German government, the state of Hessen, and industrial companies the Laboratory for Systems Engineering and Human-Machine Systems at the University of Kassel establishes an Experimental Multimedia Process Control Room. Core of this set-up are two high-performance graphics workstations linked to one of several process or vehicle simulators. Multimedia periphery includes video and teleconferencing equipment and a vibration and sound generation system.

Quality Governance based on Enterprise Engineering Method and Six Sigma Approach

Enterprise Modeling (EM) is currently in operation either as a technique to represent and understand the structure and behavior of the enterprise, or as a technique to analyze business processes, and in many cases as support technique for business process reengineering. However, EM architectures and methods for Enterprise Engineering can also used to support new management techniques like SIX SIGMA, because these new techniques need a clear, transparent and integrated definition and description of the business activities of the enterprise to be able to build up, optimize and operate an successful enterprise. The main goal of SIX SIGMA is to optimize the performance of processes. A still open question is: "What are the adequate Quality criteria and methods to ensure such performance? What must we do to get Quality governance?" This paper describes a method including an Enterprise Engineering method and SIX SIGMA strategy to reach Quality Governance

Inverse Metabolic Engineering of Synechocystis PCC 6803 for Improved Growth Rate and Poly-3-hydroxybutyrate Production

Synechocystis PCC 6803 is a photosynthetic bacterium that has the potential to make bioproducts from carbon dioxide and light. Biochemical production from photosynthetic organisms is attractive because it replaces the typical bioprocessing steps of crop growth, milling, and fermentation, with a one-step photosynthetic process. However, low yields and slow growth rates limit the economic potential of such endeavors. Rational metabolic engineering methods are hindered by limited cellular knowledge and inadequate models of Synechocystis. Instead, inverse metabolic engineering, a scheme based on combinatorial gene searches which does not require detailed cellular models, but can exploit sequence data and existing molecular biological techniques, was used to find genes that (1) improve the production of the biopolymer poly-3-hydroxybutyrate (PHB) and (2) increase the growth rate. A fluorescence activated cell sorting assay was developed to screen for high PHB producing clones. Separately, serial sub-culturing was used to select clones that improve growth rate. Novel gene knock-outs were identified that increase PHB production and others that increase the specific growth rate. These improvements make this system more attractive for industrial use and demonstrate the power of inverse metabolic engineering to identify novel phenotype-associated genes in poorly understood systems.

A process-based cost estimating tool for ship structural designs

by John M. Barentine.

Abstracting qualitative information for process supervision

Supervisory systems evolution makes the obtaining of significant information from processes more important in the way that the supervision systems' particular tasks are simplified. So, having signal treatment tools capable of obtaining elaborate information from the process data is important. In this paper, a tool that obtains qualitative data about the trends and oscillation of signals is presented. An application of this tool is presented as well. In this case, the tool, implemented in a computer-aided control systems design (CACSD) environment, is used in order to give to an expert system for fault detection in a laboratory plant

Software Development Life Cycles and Process Models

This presentation describes the evolution of Software Development Lifecycles (SDLCs) from the first formally proposed linear models including, the Waterfall (Royce 1970) through to iterative prototyping models (Spiral and Win-Win Spiral) and incremental, iterative models used in Agile Methods. We discuss the problems iinherent in each prpoosal and how successive models attempt to solve them.

TIDT's Development Process

This presentation gives an overview of TIDT's development process at time of writitng in March 2016. We were and still are developing our process. It is an agile process based on DSDM and Scrum.

Multivariate Statistical Process Control and Case-Based Reasoning for situation assessment of Sequencing Batch Reactors

ABSRACT This thesis focuses on the monitoring, fault detection and diagnosis of Wastewater Treatment Plants (WWTP), which are important fields of research for a wide range of engineering disciplines. The main objective is to evaluate and apply a novel artificial intelligent methodology based on situation assessment for monitoring and diagnosis of Sequencing Batch Reactor (SBR) operation. To this end, Multivariate Statistical Process Control (MSPC) in combination with Case-Based Reasoning (CBR) methodology was developed, which was evaluated on three different SBR (pilot and lab-scales) plants and validated on BSM1 plant layout.

Identification of resilience factors in rail engineering work

This paper discusses an ongoing project that aims at improving the potential for resilience of a system responsible for the planning of rail engineering work delivery. It focuses on the use of a human factors based approach as a way to achieve this end. In particular, the paper discusses the initial data collected by means of interviews and how this process gave way to a two fold goal: Understanding how the planning process works in reality and identifying any critical aspects of the system from a Resilience Engineering perspective. Given the nature of the process under study, information flows and communication issues have been given particular attention throughout the data collection and analysis stages. Initial data confirms that the planning process is greatly reliant on the capability of people using their knowledge and skills to communicate in a dynamic informational environment. Finally, the added value of the interviews is discussed from a human factors perspective and as a mean towards the aim of better understanding resilience in rail engineering planning.

Resilience in rail engineering work

This paper discusses an ongoing project that aims at improving the potential for resilience of a system responsible for the planning of rail engineering work delivery. This is being addressed by means of a methodology based on the observation and analysis of “real” planning activities, using resilience engineering concepts as a background. Interviews with planners have been carried out to provide an overview of the planning process and steer more in-depth investigation. Analysis of historic information and observation of planners’ main activities is underway. Given the nature of the process under study, information flows and communication issues have been given particular attention throughout the data collection and analysis stages. Initial data confirms that the planning process is greatly reliant on the capability of people using their knowledge and skills to communicate in a dynamic informational environment. Evidence was found of communication breakdowns at the boundaries of different planning levels and teams. The fact that the process is divided amongst several different areas of the organisation, often with different goals and needs, creates potential sources of conflict and tension.

Risk and price in the bidding process of contractors

Formal and analytical risk models prescribe how risk should be incorporated in construction bids. However, the actual process of how contractors and their clients negotiate and agree on price is complex, and not clearly articulated in the literature. Using participant observation, the entire tender process was shadowed in two leading UK construction firms. This was compared to propositions in analytical models and significant differences were found. 670 hours of work observed in both firms revealed three stages of the bidding process. Bidding activities were categorized and their extent estimated as deskwork (32%), calculations (19%), meetings (14%), documents (13%), off-days (11%), conversations (7%), correspondence (3%) and travel (1%). Risk allowances of 1-2% were priced in some bids and three tiers of risk apportionment in bids were identified. However, priced risks may sometimes be excluded from the final bidding price to enhance competitiveness. Thus, although risk apportionment affects a contractor’s pricing strategy, other complex, microeconomic factors also affect price. Instead of pricing in contingencies, risk was priced mostly through contractual rather than price mechanisms, to reflect commercial imperatives. The findings explain why some assumptions underpinning analytical models may not be sustainable in practice and why what actually happens in practice is important for those who seek to model the pricing of construction bids.

EnvironalPlanning: an analytical network process model for environmentally conscious construction planning

Although the construction pollution index has been put forward and proved to be an efficient approach to reducing or mitigating pollution level during the construction planning stage, the problem of how to select the best construction plan based on distinguishing the degree of its potential adverse environmental impacts is still a research task. This paper first reviews environmental issues and their characteristics in construction, which are critical factors in evaluating potential adverse impacts of a construction plan. These environmental characteristics are then used to structure two decision models for environmental-conscious construction planning by using an analytic network process (ANP), including a complicated model and a simplified model. The two ANP models are combined and called the EnvironalPlanning system, which is applied to evaluate potential adverse environmental impacts of alternative construction plans.