Cognitive Approach in Castings’ Quality Control

Every year production volume of castings grows, especially grows production volume of non-ferrous metals, thanks to aluminium. As a result, requirements to castings quality also increase. Foundry men from all over the world put all their efforts to manage the problem of casting defects. In this article the authors present an approach based on the use of cognitive models that help to visualize inner cause-and-effect relations leading to casting defects in the foundry process. The cognitive models mentioned comprise a diverse network of factors and their relations, which together thoroughly describe all the details of the foundry process and their influence on the appearance of castings’ defects and other aspects.. Moreover, the article contains an example of a simple die casting model and results of simulation. Implementation of the proposed method will help foundry men reveal the mechanism and the main reasons of casting defects formation.

Numerical modelling of complex femtosecond laser inscribed fiber gratings - comparison wih experiment

We present experimental studies and numerical modeling based on a combination of the Bidirectional Beam Propagation Method and Finite Element Modeling that completely describes the wavelength spectra of point by point femtosecond laser inscribed fiber Bragg gratings, showing excellent agreement with experiment. We have investigated the dependence of different spectral parameters such as insertion loss, all dominant cladding and ghost modes and their shape relative to the position of the fiber Bragg grating in the core of the fiber. Our model is validated by comparing model predictions with experimental data and allows for predictive modeling of the gratings. We expand our analysis to more complicated structures, where we introduce symmetry breaking; this highlights the importance of centered gratings and how maintaining symmetry contributes to the overall spectral quality of the inscribed Bragg gratings. Finally, the numerical modeling is applied to superstructure gratings and a comparison with experimental results reveals a capability for dealing with complex grating structures that can be designed with particular wavelength characteristics.

Reliability modelling and verification of manufacturing processes based on process knowledge management

Reliability modelling and verification is indispensable in modern manufacturing, especially for product development risk reduction. Based on the discussion of the deficiencies of traditional reliability modelling methods for process reliability, a novel modelling method is presented herein that draws upon a knowledge network of process scenarios based on the analytic network process (ANP). An integration framework of manufacturing process reliability and product quality is presented together with a product development and reliability verification process. According to the roles of key characteristics (KCs) in manufacturing processes, KCs are organised into four clusters, that is, product KCs, material KCs, operation KCs and equipment KCs, which represent the process knowledge network of manufacturing processes. A mathematical model and algorithm is developed for calculating the reliability requirements of KCs with respect to different manufacturing process scenarios. A case study on valve-sleeve component manufacturing is provided as an application example of the new reliability modelling and verification procedure. This methodology is applied in the valve-sleeve component manufacturing processes to manage and deploy production resources.

Sensing information modelling for smart city

Sensing technology is a key enabler of the Internet of Things (IoT) and could produce huge volume data to contribute the Big Data paradigm. Modelling of sensing information is an important and challenging topic, which influences essentially the quality of smart city systems. In this paper, the author discusses the relevant technologies and information modelling in the context of smart city and especially reports the investigation of how to model sensing and location information in order to support smart city development.

Florida Bay: Water quality status and trends, historic and emerging algal bloom problems

Florida Bay is a unique subtropical estuary that while historically oligotrophic, has been subjected to both natural and anthropogenic stressors, including hurricanes, coastal eutrophication and other impacts. These stressors have resulted in degradation of water quality in the past several decades, most evidenced by reoccurring blooms of the picocyanobacterium Synechococcus spp. Major nutrient inputs consist of freshwater flows to the eastern region from runoff and regulated canal releases, inputs from the Everglades to the central region via Taylor Slough, exchanges with the Gulf of Mexico, which include intermittent Shark River inputs to the western region, stormwater and wastewater from the Florida Keys, and atmospheric deposition. These nutrient inputs have resulted in a transition from strong phosphorus (P) limitation of phytoplankton in the eastern bay to nitrogen (N) limitation in the western bay. Large blooms of Synechococcus were most pronounced in the central bay region, in the area of transition between P and N limitation, in the mid-1990s. Although non-toxic, these blooms, which have continued intermittently through the early 2000s, resulted in significant sea-grass and benthic organism mortalities. A new suite of stressors in 2005, including the passages of Hurricanes Katrina, Rita, and Wilma, additional canal releases, and the initiation of road construction to widen the main roadway leading to the Keys, were correlated with a large Synechococcus bloom in the previously clear, strongly P- limited, northeastern region of the bay. Sustained for 3 years, this bloom was accompanied by a shift from P limitation to N limitation during its course. Nutrient bioassay experiments suggest that this bloom persisted due to the ability of Synechococcus to access organic N and P sources, microbial and geochemical cycling of organic and inorganic nutrients in the water column and between the water column and sediments (both suspended particles and benthos), and decreased grazing by benthic fauna due to their die-off.

Determining day length and temperature regulation of flowering: a molecular and modelling approach

Thesis (Ph.D.)--University of Washington, 2016-08

Three-dimensional free surface modelling in an unstructured mesh environment for metal processing applications

In the casting of metals, tundish flow, welding, converters, and other metal processing applications, the behaviour of the fluid surface is important. In aluminium alloys, for example, oxides formed on the surface may be drawn into the body of the melt where they act as faults in the solidified product affecting cast quality. For this reason, accurate description of wave behaviour, air entrapment, and other effects need to be modelled, in the presence of heat transfer and possibly phase change. The authors have developed a single-phase algorithm for modelling this problem. The Scalar Equation Algorithm (SEA) (see Refs. 1 and 2), enables the transport of the property discontinuity representing the free surface through a fixed grid. An extension of this method to unstructured mesh codes is presented here, together with validation. The new method employs a TVD flux limiter in conjunction with a ray-tracing algorithm, to ensure a sharp bound interface. Applications of the method are in the filling and emptying of mould cavities, with heat transfer and phase change.

Biogeochemical response of Tagus Estuary to climate change : a modelling study

Estuaries are highly dynamic systems which may be modified in a climate change context. These changes can affect the biogeochemical cycles. Among the major impacts of climate change, the increasing rainfall events and sea level rise can be considered. This study aims to research the impact of those events in biogeochemical dynamics in the Tagus Estuary, which is the largest and most important estuary along the Portuguese coast. In this context a 2D biophysical model (MOHID) was implemented, validated and explored, through comparison with in-situ data. In order to study the impact of extreme rainfall events, which can be characterized by an high increase in freshwater inflow, three scenarios were set by changing the inputs from the main tributaries, Tagus and Sorraia Rivers. A realistic scenario considering one day of Tagus and Sorraia River extreme discharge, a scenario considering one day of single extreme discharge of the Tagus River and finally one considering the extreme runoff just from Sorraia River. For the mean sea level rise, two scenarios were also established. The first with the actual mean sea level value and the second considering an increase of 0.42 m. For the extreme rainfall events simulations, the results suggest that the biogeochemical characteristics of the Tagus Estuary are mainly influenced by Tagus River discharge. For sea level rise scenario, the results suggest a dilution in nutrient concentrations and an increase in Chl-a in specific areas.For both scenarios, the suggested increase in Chl-a concentration for specific estuarine areas, under the tested scenarios, can lead to events that promote an abnormal growth of phytoplankton (blooms) causing the water quality to drop and the estuary to face severe quality issues risking all the activities that depend on it.

BIORETENTION/CISTERN/IRRIGATION TO ELIMINATE STORMWATER RUNOFF AT THE UNIVERSITY OF MARYLAND

Water quality of parking lot (~1,858 m2) stormwater runoff and its treated effluent flow were analyzed for total phosphorus (TP), total nitrogen (TN), total suspended solids (TSS), electrical conductivity (EC), copper, lead and zinc. The novel system under investigation, located at the University of Maryland, College Park, Maryland, includes a standard bioretention facility, underdrained to a cistern to store treated stormwater, and pumped to a vegetable garden for irrigation. The site abstraction, the average bioretention abstraction, and bowl volumes were estimated to be 8500, 4378, and 895 L, respectively; this indicates that rain events of more than 0.45 cm are necessary to produce runoff and more than 0.75 cm will produce system overflow. The cistern water quality indicates good-to-excellent treatment by the system. Compared to local tap water, cistern water has lower concentrations of TP, TN, EC (non-winter), copper, and zinc, indicating a good water source for irrigation.

An Integrated approach to street canyon pollution modelling.

An integrated method for the prediction of the spatial pollution distribution within a street canyon directly from a microscopic traffic simulation model is outlined. The traffic simulation package Paramics is used to model the flow of vehicles in realistic traffic conditions on a real road network. This produces details of the amount of pollutant produced by each vehicle at any given time. The authors calculate the dispersion of the pollutant using a particle tracking diffusion method which is superimposed on a known velocity and turbulence field. This paper shows how these individual components may be integrated to provide a practical street canyon pollution model. The resulting street canyon pollution model provides isoconcentrations of pollutant within the road topography.

The Role of decision-analytic modelling in German health technology assessments

BACKGROUND: Decision-analytic modelling (DAM) has become a widespread method in health technology assessments (HTA), but the extent to which modelling is used differs among international HTA institutions. In Germany, the use of DAM is optional within HTAs of the German Institute of Medical Documentation and Information (DIMDI). Our study examines the use of DAM in DIMDI HTA reports and its effect on the quality of information provided for health policies. METHODS: A review of all DIMDI HTA reports (from 1998 to September 2012) incorporating an economic assessment was performed. All included reports were divided into two groups: HTAs with DAM and HTAs without DAM. In both groups, reports were categorized according to the quality of information provided for healthcare decision making. RESULTS: Of the sample of 107 DIMDI HTA reports, 17 (15.9%) used DAM for economic assessment. In the group without DAM, conclusions were limited by the quality of economic information in 51.1% of the reports, whereas we did not find limited conclusions in the group with DAM. Furthermore, 24 reports without DAM (26.7%) stated that using DAM would likely improve the quality of information of the economic assessment. CONCLUSION: The use of DAM techniques can improve the quality of HTAs in Germany. When, after a systematic review of existing literature within a HTA, it is clear that DAM is likely to positively affect the quality of the economic assessment DAM should be used.

Regenerative Stormwater Conveyance: Design Implications of an Urban Case Demonstration in Baltimore, Maryland

This research-design thesis explores the implementation of Regenerative Stormwater Conveyance (RSC) as a retrofit of an existing impervious drainage system in a small catchment in the degraded Jones Falls watershed in Baltimore City. An introduction to RSC is provided, placing its development within a theoretical context of novel ecosystems, biomimicry and Nassauer and Opdam’s (2008) model of landscape innovation. The case site is in Baltimore’s Hampden neighborhood on City-owned land adjacent to rowhomes, open space and an access point to a popular wooded trail along a local stream. The design proposal employs RSC to retrofit an ill-performing stormwater system, simultaneously providing a range of ecological, social and economic services; water quantity, water quality and economic performance of the proposed RSC are quantified. While the proposed design is site-specific the model is adaptable for retrofitting other small-scale impervious drainage systems, providing a strategic tool in addressing Baltimore City’s stormwater challenges.

Modelling of an efficient dynamic smart solar photovoltaic power grid system

A smart solar photovoltaic grid system is an advent of innovation coherence of information and communications technology (ICT) with power systems control engineering via the internet [1]. This thesis designs and demonstrates a smart solar photovoltaic grid system that is selfhealing, environmental and consumer friendly, but also with the ability to accommodate other renewable sources of energy generation seamlessly, creating a healthy competitive energy industry and optimising energy assets efficiency. This thesis also presents the modelling of an efficient dynamic smart solar photovoltaic power grid system by exploring the maximum power point tracking efficiency, optimisation of the smart solar photovoltaic array through modelling and simulation to improve the quality of design for the solar photovoltaic module. In contrast, over the past decade quite promising results have been published in literature, most of which have not addressed the basis of the research questions in this thesis. The Levenberg-Marquardt and sparse based algorithms have proven to be very effective tools in helping to improve the quality of design for solar photovoltaic modules, minimising the possible relative errors in this thesis. Guided by theoretical and analytical reviews in literature, this research has carefully chosen the MatLab/Simulink software toolbox for modelling and simulation experiments performed on the static smart solar grid system. The auto-correlation coefficient results obtained from the modelling experiments give an accuracy of 99% with negligible mean square error (MSE), root mean square error (RMSE) and standard deviation. This thesis further explores the design and implementation of a robust real-time online solar photovoltaic monitoring system, establishing a comparative study of two solar photovoltaic tracking systems which provide remote access to the harvested energy data. This research made a landmark innovation in designing and implementing a unique approach for online remote access solar photovoltaic monitoring systems providing updated information of the energy produced by the solar photovoltaic module at the site location. In addressing the challenge of online solar photovoltaic monitoring systems, Darfon online data logger device has been systematically integrated into the design for a comparative study of the two solar photovoltaic tracking systems examined in this thesis. The site location for the comparative study of the solar photovoltaic tracking systems is at the National Kaohsiung University of Applied Sciences, Taiwan, R.O.C. The overall comparative energy output efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic monitoring system as observed at the research location site is about 72% based on the total energy produced, estimated money saved and the amount of CO2 reduction achieved. Similarly, in comparing the total amount of energy produced by the two solar photovoltaic tracking systems, the overall daily generated energy for the month of July shows the effectiveness of the azimuthal-altitude tracking systems over the 450 stationary solar photovoltaic system. It was found that the azimuthal-altitude dual-axis tracking systems were about 68.43% efficient compared to the 450 stationary solar photovoltaic systems. Lastly, the overall comparative hourly energy efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic energy system was found to be 74.2% efficient. Results from this research are quite promising and significant in satisfying the purpose of the research objectives and questions posed in the thesis. The new algorithms introduced in this research and the statistical measures applied to the modelling and simulation of a smart static solar photovoltaic grid system performance outperformed other previous works in reviewed literature. Based on this new implementation design of the online data logging systems for solar photovoltaic monitoring, it is possible for the first time to have online on-site information of the energy produced remotely, fault identification and rectification, maintenance and recovery time deployed as fast as possible. The results presented in this research as Internet of things (IoT) on smart solar grid systems are likely to offer real-life experiences especially both to the existing body of knowledge and the future solar photovoltaic energy industry irrespective of the study site location for the comparative solar photovoltaic tracking systems. While the thesis has contributed to the smart solar photovoltaic grid system, it has also highlighted areas of further research and the need to investigate more on improving the choice and quality design for solar photovoltaic modules. Finally, it has also made recommendations for further research in the minimization of the absolute or relative errors in the quality and design of the smart static solar photovoltaic module.

Advanced parametrical modelling of 24 GHz radar sensor IC packaging components

This paper deals with the development of an advanced parametrical modelling concept for packaging components of a 24 GHz radar sensor IC used in automotive driver assistance systems. For fast and efficient design of packages for system-in-package modules (SiP), a simplified model for the description of parasitic electromagnetic effects within the package is desirable, as 3-D field computation becomes inefficient due to the high density of conductive elements of the various signal paths in the package. By using lumped element models for the characterization of the conductive components, a fast indication of the design's signal-quality can be gained, but so far does not offer enough flexibility to cover the whole range of geometric arrangements of signal paths in a contemporary package. This work pursues to meet the challenge of developing a flexible and fast package modelling concept by defining parametric lumped-element models for all basic signal path components, e.g. bond wires, vias, strip lines, bumps and balls. © Author(s) 2011. CC Attribution 3.0 License.

Water Quality Impacts due to the Addition of Biosolids-Derived Compost to Bioretention

Bioretention is a common stormwater control measure (SCM). While compost, combined with other bioretention soil media (BSM), has the potential for increased pollutant and water uptake and storage, it also may leach harmful nutrients. Limited information is available on the use of compost in SCMs. Therefore, this project seeks to analyze the impacts of the addition of biosolids-derived compost to bioretention. To accomplish this, bioretention mesocosm column studies were conducted to determine the leaching effects of 15%, 30%, and 30% tap water-washed compost, mixed with standard BSM. Synthetic storm runoff was applied to the columns and the effluent was analyzed for total nitrogen (N), phosphorus (P), and their speciation. All three columns leached N and P with maximum total N concentrations of 2,200, 2,100, and 300 mg-N/L and total P concentrations of 12, 4.9, and 4.6 mg-P/L for the 30%, 15%, and 30% washed mesocosms, respectively. Therefore, based on this study, it is not recommended that biosolids-derived compost be added to bioretention media.