Summary of FY 2010 Iodine Capture Studies at the INL

Three breakthrough runs using silver mordenite sorbents were conducted and a dynamic sorption capacity estimated based on MeI analysis from a 2" bed. However, it is now believed the data for the first 2 runs is incomplete because the contributions from elemental iodine were not included. Although the only source of iodine was MeI, elemental iodine was generated within the sorbent bed, presumably from a recombination reaction likely catalyzed by silver mordenite. On-line effluent analysis with a GC was only capable of analyzing MeI, not I2. Scrub samples drawn during Run #3, which are specific for I2, show significant levels of I2 being emitted from a partially spent Ag-mordenite bed. By combining MeI and I2 analyses, a well defined total iodine breakthrough curve can be generated for Run #3. At the conclusion of Run #3 (IONEX Ag-900 was the sorbent) the effluent level from Bed 2 was approaching 70% of the feed concentration. The leading bed (Bed 1) had an estimated average loading of 66 mg I/g sorbent, Bed 2's was 52 mg I/g. The corresponding silver utilizations (assuming formation of AgI) were about 59% and 46%, respectively. The spent sorbents are being sent to Sandia National Laboratories for confirmatory analysis of iodine and silver utilization as well as source material for waste form development

Integrated and Modular Didactic and Methodological Concept for a Learning Factory

AbstractAs today manufacturing is not only subject to a single factory, but a network of globally distributed production sites, the goal-oriented encouragement of professional capacities is the motivation for the Learning Factory on Global Production (LGP). In this context, the design of a competency-based and action-oriented didactic and methodological concept is a prerequisite for sustainable learning results and for the development of self-determined problem solving skills. The presented paper gives an overview to the didactic and methodological design approach of the LGP. The integrated modular concept of e-learning and application in the learning factory environment supports self-directed learning and implemented by structuring the teaching/ learning process according to the model of complete action

Process model for the successful implementation and demonstration of SME-based industry 4.0 showcases in global production networks

Small and medium-sized enterprises (SMEs), many of which operate as suppliers in global production networks (GPN), often times lack behind large enterprises in terms of Industry 4.0 implementation. For this reason, scientific contributions recommend SMEs to approach Industry 4.0 through pilot projects in which individual Industry 4.0 use cases are developed and implemented. Hence, to allow for a targeted development and implementation of Industry 4.0 use cases for SMEs in GPN, this paper proposes a five-step process model that seeks to make use of Industry 4.0 potentials in terms of increased product qualities and logistics performances within such networks. In contrast to existing process models, this paper follows a holistic approach that initially focuses on the identification of potential problems that impede increased product qualities and logistics performances. Building upon these problems, potential Industry 4.0 solutions are derived and transferred into use cases using a structured idea generation and selection process. After the successful implementation of the use case, the procedure is completed by the conversion of the use case into a showcase that might serve as a lighthouse project illustrating the potentials of Industry 4.0 for other production network partners. For testing its practicability, the procedure is exemplarily applied to the GPN of an automotive supplier

A Modality-Specific Feedforward Component of Choice-Related Activity in MT

The activity of individual sensory neurons can be predictive of an animal\u27s choices. These decision signals arise from network properties dependent on feedforward and feedback inputs; however, the relative contributions of these inputs are poorly understood. We determined the role of feedforward pathways to decision signals in MT by recording neuronal activity while monkeys performed motion and depth tasks. During each session, we reversibly inactivated V2 and V3, which provide feedforward input to MT that conveys more information about depth than motion. We thus monitored the choice-related activity of the same neuron both before and during V2/V3 inactivation. During inactivation, MT neurons became less predictive of decisions for the depth task but not the motion task, indicating that a feedforward pathway that gives rise to tuning preferences also contributes to decision signals. We show that our data are consistent with V2/V3 input conferring structured noise correlations onto the MT population

Augmented Go & See: An approach for improved bottleneck identification in production lines

Bottlenecks in production lines are often shifting and thus hard to identify. They lead to decreased output, longer throughput times and higher work in progress. Go & See is a well-established Lean practice where managers go to the shop floor to see the problems first hand. Mixed reality is a promising technology to improve transparency in complex production environments. Until recently, mixed reality applications have been very demanding in terms of computing power requiring high performance hardware. This paper presents an approach for real-time KPI visualization using mixed reality for bottleneck identification in production lines relying on the bring-your-own device principle. The developed application uses image recognition to identify work stations and visualizes cycle times and work in progress in augmented reality. With this additional information, it is possible to discern different root causes for bottlenecks, for example systematically higher or varying cycle times due to breakdowns. This solution can be classified according to the acatech industry 4.0 maturity model as a level 3 - transparency - application. It could be shown that the identification of bottlenecks and underlying reasons has been improved compared to standard Go & See

Consolidated financial statements

The Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311

Consolidated financial statements

The Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311