Modeling and Simulation of Metallurgical Processes in Ironmaking and Steelmaking

In recent years, improving the sustainability of the steel industry and reducing its CO2 emissions has become a global focus. To achieve this goal, further process optimization in terms of energy and resource efficiency and the development of new processes and process routes are necessary. Modeling and simulation have established themselves as invaluable sources of information for otherwise unknown process parameters and as an alternative to plant trials that involves lower costs, risks, and time. Models also open up new possibilities for model-based control of metallurgical processes. This Special Issue focuses on recent advances in the modeling and simulation of unit processes in iron and steelmaking. It includes reviews on the fundamentals of modeling and simulation of metallurgical processes, as well as contributions from the areas of iron reduction/ironmaking, steelmaking via the primary and secondary route, and continuous casting

Text Similarity Between Concepts Extracted from Source Code and Documentation

Context: Constant evolution in software systems often results in its documentation losing sync with the content of the source code. The traceability research field has often helped in the past with the aim to recover links between code and documentation, when the two fell out of sync. Objective: The aim of this paper is to compare the concepts contained within the source code of a system with those extracted from its documentation, in order to detect how similar these two sets are. If vastly different, the difference between the two sets might indicate a considerable ageing of the documentation, and a need to update it. Methods: In this paper we reduce the source code of 50 software systems to a set of key terms, each containing the concepts of one of the systems sampled. At the same time, we reduce the documentation of each system to another set of key terms. We then use four different approaches for set comparison to detect how the sets are similar. Results: Using the well known Jaccard index as the benchmark for the comparisons, we have discovered that the cosine distance has excellent comparative powers, and depending on the pre-training of the machine learning model. In particular, the SpaCy and the FastText embeddings offer up to 80% and 90% similarity scores. Conclusion: For most of the sampled systems, the source code and the documentation tend to contain very similar concepts. Given the accuracy for one pre-trained model (e.g., FastText), it becomes also evident that a few systems show a measurable drift between the concepts contained in the documentation and in the source code.</p

NASA/ASEE Summer Faculty Fellowship Program

This document is a collection of technical reports on research conducted by the participants in the 1992 NASA/ASEE Summer Faculty Fellowship Program at Kennedy Space Center (KSC). This was the eighth year that a NASA/ASEE program has been conducted at KSC. The 1992 program was administered by the University of Central Florida in cooperation with KSC. The program was operated under the auspices of the American Society for Engineering Education (ASEE) with sponsorship and funding from the Office of Educational Affairs, NASA Headquarters, Washington, D.C. The KSC program was one of nine such Aeronautics and Space Research Programs funded by NASA Headquarters in 1992. The basic common objectives are to further the professional knowledge, to stimulate an exchange of ideas, to enrich and refresh the research and teaching activities, and to contribute to the research objectives of the NASA centers

Testing the capability of Rare Earth Elements to identify archaeological strata in an African site: The case of the terraced landscape at Konso, Ethiopia

Over the last twenty years Rare Earth Elements (REE) have started to be part of archaeometric studies. Due to their particular characteristics there have been several attempts to apply REE analysis to different archaeological scenarios including stratigraphically-controlled agricultural soils, demonstrating that this is an effective tool to understand how human activity is reflected in soil development. Our study proposes a new methodological approach for the identification of anthropogenic deposits through REE soil analysis, pushing current limitations of traditional chemical and sedimentology techniques. Our study represents the first application of REE concentrations in soils from tropical Africa within an archaeological context. The agricultural soils were captured in an artificial sediment trap that forms part of the terraced landscape in Konso, Ethiopia; a system thought to have developed over the last 500 years, and which was awarded World Heritage status in 2011. Forty samples were taken from successive alluvial layers down a c. 2m thick soil sequence that had accumulated behind a series of drystone walls. The samples were analyzed for trace elements and REE via ICP-MS. To understand the causes of enrichment or depletion of REE, the data were compared with soil organic matter, organic carbon and fire markers. To aid interpretation we crossreferenced our results with archaeobotanical and soil micromorphology data. Data were analysed using multivariate statistics. Taken together these results present a very different picture of landscape development to previous presented accounts; the REE analyses provide significant details regarding the source and transportation of sediments

Machine Learning in Tribology

Tribology has been and continues to be one of the most relevant fields, being present in almost all aspects of our lives. The understanding of tribology provides us with solutions for future technical challenges. At the root of all advances made so far are multitudes of precise experiments and an increasing number of advanced computer simulations across different scales and multiple physical disciplines. Based upon this sound and data-rich foundation, advanced data handling, analysis and learning methods can be developed and employed to expand existing knowledge. Therefore, modern machine learning (ML) or artificial intelligence (AI) methods provide opportunities to explore the complex processes in tribological systems and to classify or quantify their behavior in an efficient or even real-time way. Thus, their potential also goes beyond purely academic aspects into actual industrial applications. To help pave the way, this article collection aimed to present the latest research on ML or AI approaches for solving tribology-related issues generating true added value beyond just buzzwords. In this sense, this Special Issue can support researchers in identifying initial selections and best practice solutions for ML in tribology

Play Among Books

How does coding change the way we think about architecture? Miro Roman and his AI Alice_ch3n81 develop a playful scenario in which they propose coding as the new literacy of information. They convey knowledge in the form of a project model that links the fields of architecture and information through two interwoven narrative strands in an “infinite flow” of real books

Hydrogen Embrittlement of Automotive Ultra-High-Strength Steels: Mechanism and Minimisation

Automotive manufacturers are increasingly using ultra-high-strength steels in vehicle components to facilitate mass reduction via downgauging. Unfortunately, as the strength of steels increases, so does susceptibility to ‘hydrogen embrittlement’, a process in which ductility is significantly impaired by ingress of hydrogen. Mechanisms and environmental conditions by which this degradation occurs are not fully understood. In this work, 2 fully-ferritic, 2 fully-martensitic boron, and 2 ferrite-martensite dual-phase, ultra-high-strength steels, were assessed for susceptibility to hydrogen embrittlement via 3 key characteristics: firstly, with particular regard to hydrogen evolution under corrosion conditions, through well-established open circuit potential and potentiodynamic polarisation experiments. Exacerbation of hydrogen evolution through galvanic corrosion of a zinc coating was assessed by scanning vibrating electrode technique (SVET), and an attempt made to quantify increased risk of hydrogen evolution during crevice corrosion through a novel time-lapse photography experiment. Secondly, hydrogen diffusivity was assessed via permeation experiments. Finally, degradation in mechanical properties due to diffusing hydrogen was evaluated through slow strain rate tests (SSRT), whereby susceptibility to embrittlement was equated to reduction in ductility of hydrogen-charged test specimens. The fully-ferritic steels showed the greatest resistance to mechanical degradation, attributed to micro-alloy nano-precipitates within their microstructure acting as ‘traps’, leading to lower diffusivity compared to dual-phase steels of equivalent strength. Indeed, lower diffusivity showed a strong correlation with lower levels of embrittlement across all steels. 1000 MPa dual-phase steel showed the greatest degradation in mechanical properties, with fully-martensitic boron steels also found to be particularly susceptible. 1000 MPa dual-phase steel also showed the largest increase in hydrogen evolution reaction in response to polarisation, thought to result from the inherent potential difference between ferrite and martensite phases. Galvanic corrosion of a damaged zinc coating was found to polarise the exposed steel substrate, triggering sufficient hydrogen evolution to reach critical concentrations for embrittlement

Production of Commodities and Iron Economy in Early China: A Case Study of a Western Han Iron Foundry at Taicheng

How the exchange of commodities and control over resources shaped the social world is a major concern in anthropology. In the domain of history, the form and structure of market economy during the Han period is also a long debated issue. Consequently, the study of imperial control over commodities within an anthropological framework is a promising avenue that sheds new light on debates about the Han commodity economy. This dissertation addresses the production and distribution system of the Han iron industry in order to investigate the nature of commodities and resource control. This project integrates metallurgical and zooarchaeological approaches to analyzing manufacturing remains at an iron foundry site named Taicheng, as well as iron objects from various cemeteries in the Guanzhong basin, Shaanxi, the capital area of the Western Han Empire (202 BCE-9 CE). The results provide new evidence demonstrating the “commodity economy” of iron in the capital area, in fact, functioned as a multi-level network system. Even within the same category of iron products, the degree of commodification and the scope of market networks widely varied in the Western Han period, a fact that has been overlooked in previous literature. In addition, the transportation of iron goods to the capital created a massive market network connecting different parts of the Empire and generated the momentum for the capital to dominate over its eastern territory.Anthropolog

NASA Tech Briefs, December 1988

This month's technical section includes forecasts for 1989 and beyond by NASA experts in the following fields: Integrated Circuits; Communications; Computational Fluid Dynamics; Ceramics; Image Processing; Sensors; Dynamic Power; Superconductivity; Artificial Intelligence; and Flow Cytometry. The quotes provide a brief overview of emerging trends, and describe inventions and innovations being developed by NASA, other government agencies, and private industry that could make a significant impact in coming years. A second bonus feature in this month's issue is the expanded subject index that begins on page 98. The index contains cross-referenced listings for all technical briefs appearing in NASA Tech Briefs during 1988

NASA Tech Briefs, November 1993

Topics covered: Advanced Manufacturing; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Sciences; Life Sciences