A Coupling Algorithm of Computational Fluid and Particle Dynamics (CFPD)

Computational fluid dynamics (CFD) and particle hydrodynamics (PHD) have been developed almost independently. CFD is classified into Eulerian and Lagrangian. The Eulerian approach observes fluid motion at specific locations in the space, and the Lagrangian approach looks at fluid motion where the observer follows an individual fluid parcel moving through space and time. In classical mechanics, particle dynamic simulations include molecular dynamics, Brownian dynamics, dissipated particle dynamics, Stokesian dynamics, and granular dynamics (often called discrete element method). Dissipative hydrodynamic method unifies these dynamic simulation algorithms and provides a general view of how to mimic particle motion in gas and liquid. Studies on an accurate and rigorous coupling of CFD and PHD are in literature still in a growing stage. This chapter shortly reviews the past development of CFD and PHD and proposes a general algorithm to couple the two dynamic simulations without losing theoretical rigor and numerical accuracy of the coupled simulation

Dissipative Dynamics of Granular Materials

Granules are inelastic particles, undergoing dissipative and repulsive forces on contact. A granular state consists of a conglomeration of discrete, non-Brownian particles in a combined state of solid, liquid, and gas. Modern theoretical physics lacks general theories for the granular states. Simulation methods for particle dynamics include molecular dynamics (MD), Brownian dynamics (BD), Stokesian dynamics (SD), dissipative particle dynamics (DPD), and dissipative hydrodynamics (DHD). These conventional methods were originally designed to mimic the small-particle motion being less influenced by the gravitational force. There are three reasons that a conventional method cannot be directly applied to investigate granular dynamics. First, volume exclusion forces between colliding particles are often disregarded due to strong repulsive forces between negatively charged colloids and nanoparticles. Second, the gravitational force is not significant as applied to small, light particles, and therefore it is often discarded in force/torque calculations. Third, energy conservation in an equilibrium state is not guaranteed for the granular system due to the inelastic and frictional nature of the granular materials. In this light, this chapter discusses the fundamentals of particle dynamics methods, formulates a robust theoretical framework for granular dynamics, and discusses the current applications and future directions of computational granular dynamics

Influence of Al and Mn additions on the microstructure and corrosion properties of extruded Mg–8Sn–1Zn alloys

Department of Materials Science EngineeringThe microstructure and corrosion properties of extruded Mg–8Sn–1Zn alloys with varying Al contents were investigated. The microstructures of the extruded alloys mainly consisted of α-Mg grains and Mg2Sn particles in common. The addition of Al to the ternary alloy resulted in the formation of different types of Al–Fe-based intermetallic particles depending on Al contents. Corrosion rates were found to be drastically increased by additions of 1 – 3wt% Al. The extruded alloys with 1 – 3wt% Al showed over 30 times higher corrosion rates than those containing less than 0.3wt% Al in 0.6 M NaCl solution. The increase in corrosion rate produced by the Al addition was attributed to the presence of Al5Fe2 particles, which act as strong cathodic sites for H2 evolution during corrosion. In addition, a solution to reduce the high corrosion rate of the Mg–8Sn–1Zn alloys containing Al is suggested. The presence of Al5Fe2 particles, having deleterious effect on corrosion resistance, can be replaced by that of Al8Mn5 particles by the addition of Mn to the Mg–8Sn–1Zn alloys with 1 – 3wt% Al. The Mg–8Sn–1Zn–1Al alloy with 0.1wt%Mn showed over an order lower corrosion rate than the quaternary alloy without Mn, which can be attributed to the relatively sluggish cathodic reaction in the presence of Al8Mn5 particles.ope

Numerical Modeling Of OTEC Thermal Discharges In Coastal Waters

Thermal discharge from industrial outfalls is categorized into two major classes based on their density. First class is the effluent that has a higher density than that of the ambient water body. The second class is the effluent that has a lower density than that of the ambient water body. Due to the effect of several factors such as tides, waves, winds, river discharges, thermal effluents etc., the mixing characteristics of OTEC (Ocean Thermal Energy Conversion) thermal plume is much complicated. In this study we try to identify the mixing and dispersion characteristics of coastal waters to consider their physical properties using a field observation and a three-dimensional numerical modeling with FVM (Finite Volume Method). A plume model and observed CTD data was used to predict the mixing behavior of thermal discharges in coastal waters. The elevation, current, temperature and salinity boundary conditions on the open boundary and thermal effluents at the specific boundary are considered in this study. Various turbulence models have been applied in the numerical model to assess the accuracy of turbulence models in predicting the effluent discharges in submerged outfalls. The model successfully reproduced well known the plume behavior in coastal waters. These works illustrate the challenging nature of OTEC environmental studies. Keywords : Ocean Thermal Energy Conversion, Finite Volume Method, Plume Mode

Design principles for transforming making programs into online settings at public libraries

Purpose This paper aims to investigate design principles for transforming existing making communities of practice within public libraries into online knowledge-building communities to support youths, families with young children and adult members’ making and tinkering during COVID-19. Design/methodology/approach Building upon C4P and connected learning framework, the authors analyze existing literature and practitioner reports on informal learning projects related to making and STEM learning, family learning and online learning as well as emergent cases of innovative approaches in response to COVID-19 from public libraries, informal learning institutions and community groups. Findings The authors suggest 11 design principles around five areas: program design, facilitation, tools and materials, process documentation and sharing and feedback. Originality/value This work contributes to the information and learning sciences concerned with community engagement and knowledge creation by suggesting a design model to transform and sustain existing making communities of practice within public libraries into online knowledge-building communities during COVID-19

An Empirical Examination of Consumer Behavior for Search and Experience Goods in Sentiment Analysis

With the explosive increase of user-generated content such as product reviews and social media, sentiment analysis has emerged as an area of interest. Sentiment analysis is a useful method to analyze product reviews, and product feature extraction is an important task in sentiment analysis, during which one identifies features of products from reviews. Product features are categorized by product type, such as search goods or experience goods, and their characteristics are totally different. Thus, we examine whether the classification performance differs by product type. The findings show that the optimal threshold varies by product type, and simply decreasing the threshold to cover many features does not guarantee improvement of the classification performance

Can Ocean Thermal Energy Conversion and Seawater Utilisation Assist Small Island Developing States? A Case Study of Kiribati, Pacific Islands Region

The deployment of a land-based Ocean Thermal Energy Conversion (OTEC) plant in South Tarawa, Kiribati, Pacific Islands Region, in 2020/2021, represents a major technical achievement, alongside an international development opportunity. Pacific Small Island Developing States (PSIDS) are archipelago nations with small land areas and large oceanic exclusive economic zones. Geographical isolation and large transport distances make economic development a challenge. A lack of affordable and reliable energy in many PSIDS is a development inhibitor. PSIDS are situated within the areas of highest ocean thermal potential in the world. Temperature differences between surface and 1 km depth waters, are in excess of 24°C. Regional geology and tectonics allow access to deeper, colder, waters within few kilometres of many shorelines, and close to market. Seawater Utilization technologies can catalyse varied industrial development (e.g., fresh water/aquaculture/agriculture/mineral salts). The KRISO (Korean Research Institute of Ships and Ocean Engineering)-Government of Kiribati OTEC partnership is already 7 years old (2013–2020) and has involved extensive negotiations, awareness raising programmes, and inclusive collaboration. The project will test OTEC technologies and explore a range development opportunities for Kiribati. The programme could become a role model for the application of the concept of ‘Interconnected Geoscience’

Retrieval of NO2 Column Amounts from Ground-Based Hyperspectral Imaging Sensor Measurements

Total column amounts of NO2 (TCN) were estimated from ground-based hyperspectral imaging sensor (HIS) measurements in a polluted urban area (Seoul, Korea) by applying the radiance ratio fitting method with five wavelength pairs from 400 to 460 nm. We quantified the uncertainty of the retrieved TCN based on several factors. The estimated TCN uncertainty was up to 0.09 Dobson unit (DU), equivalent to 2.687 ?? 1020 molecules m???2) given a 1?? error for the observation geometries, including the solar zenith angle, viewing zenith angle, and relative azimuth angle. About 0.1 DU (6.8%) was estimated for an aerosol optical depth (AOD) uncertainty of 0.01. In addition, the uncertainty due to the NO2 vertical profile was 14% to 22%. Compared with the co-located Pandora spectrophotometer measurements, the HIS captured the temporal variation of the TCN during the intensive observation period. The correlation between the TCN from the HIS and Pandora also showed good agreement, with a slight positive bias (bias: 0.6 DU, root mean square error: 0.7 DU)