ADVANCED CUTTINGS TRANSPORT STUDY

This is the second quarterly progress report for Year-4 of the ACTS Project. It includes a review of progress made in: (1) Flow Loop construction and development and (2) research tasks during the period of time between October 1, 2002 and December 30, 2002. This report presents a review of progress on the following specific tasks. (a) Design and development of an Advanced Cuttings Transport Facility Task 3: Addition of a Cuttings Injection/Separation System, Task 4: Addition of a Pipe Rotation System. (b) New research project (Task 9b): ''Development of a Foam Generator/Viscometer for Elevated Pressure and Elevated Temperature (EPET) Conditions''. (d) Research project (Task 10): ''Study of Cuttings Transport with Aerated Mud Under Elevated Pressure and Temperature Conditions''. (e) Research on three instrumentation tasks to measure: Cuttings concentration and distribution in a flowing slurry (Task 11), Foam texture while transporting cuttings. (Task 12), and Viscosity of Foam under EPET (Task 9b). (f) New Research project (Task 13): ''Study of Cuttings Transport with Foam under Elevated Pressure and Temperature Conditions''. (g) Development of a Safety program for the ACTS Flow Loop. Progress on a comprehensive safety review of all flow-loop components and operational procedures. (Task 1S). (h) Activities towards technology transfer and developing contacts with Petroleum and service company members, and increasing the number of JIP members

Modelling land use using demographic forecasting and local optimisation: A case study of general education provision in Riyadh, Saudi Arabia

Globally accepted guidelines for land use allocation in Riyadh, Saudi Arabia have been based on an outmoded practice that was created over a century ago. This approach is based on a mix of predetermined population densities, walking distances, and per person area ratios. The latter criterion is essentially based on a worldwide average for facility areas and user numbers. The fundamental criticism levelled at such practices is their insensitivity to population trends and limited land resources. In this context, this research is aimed at updating common practice in the light of population growth and residential mobility projections at the city and district levels. The models introduced aim to provide comprehensive and adaptable simulation tools for optimising any type of land use provision standard over a specified time period. The simulation environment makes use of an agent-based framework that adapts and integrates a number of well-known methodologies, including Cohort Component Modelling (CCM) for population projection, Spatial Interaction (SI) modelling for residential mobility, and AutoRegressive Integrated Moving Average (ARIMA) for various ratio extrapolation. Additionally, new hybrid concepts and approaches have been evaluated, including a household based CCM and the use of Neural Network algorithms (NN) to forecast residential mobility. The case study focuses on Saudi populations in Riyadh, Saudi Arabia where the three general education stages at elementary, middle, and secondary levels were optimised for both genders. Moreover, the optimisation time horizon spans 50 years, from 2020 to 2070 while the focus of research at the city level optimises the conventional ratio of area per student based on the present stock of education allocated land and a land consumption ratio defined for every five years. The district level optimisation, on the other hand, balances the demand and supply of education over 50 years by utilising the Ministry of Education's (MOE) predesigned school prototypes. The research findings demonstrate the feasibility of developing a tool for optimising land use guidelines that is capable of producing acceptable outcomes while being sensitive to demographic change and land resource availability

Sensitivity analysis of Repast computational ecology models with R/Repast

Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual-based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities or populations due to individual variability. In addition, being a bottom up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in silico experimental setup. In this paper we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results

Sensitivity analysis of Repast computational ecology models with R/Repast

Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual-based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities, or populations due to individual variability. In addition, being a bottom-up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course, no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in-silico experimental setup. In this article, we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results

Smart risk management : a guide to identifying and calibrating business risks

https://egrove.olemiss.edu/aicpa_guides/2714/thumbnail.jp

Investigating The Dynamics of Hepatic Inflammation Through Simulation

Inflammation is a fundamental mechanism for the body to induce repair and healing in tissues, and exacerbated inflammatory responses are associated with a wide variety of diseases and disorders. Categorising the various cells, proteins, and precise mechanisms involved in initiating and driving inflammation poses significant challenges, due to the complex interplay that occurs between them. In this thesis, I will introduce a deadly parasitic disease called Visceral Leishmaniasis (VL) as a case study in using computational modelling techniques to elucidate the mechanisms underpinning inflammation. During VL infection, inflammatory aggregations of immune system cells form, these are called granulomas. Granulomas function to contain and subsequently remove infection. Whilst immunological studies have provided insights into the structure and function of granulomas, there remains a breadth of questions which laboratory techniques are currently incapable of answering. As such, the challenges facing biologists from a scientific perspective will be addressed, I will then argue after a thorough review of the relevant literature, that agent-based computational modelling is a logical choice for research into granuloma formation, and that such models can help answer some outstanding questions in the field. The thesis presents the process of designing and developing the first spatially resolved model of liver localised granuloma formation during VL. The development and use of modelling and simulation to study granulomas has involved close collaboration with immunologists at all stages through conceptualisation, modelling, implementation, and also results interpretation. I describe the use of established statistical techniques to instill confidence in both the model, and the results it can produce through simulation. Through iterative hypothesis generation and testing, the research undertaken has allowed for several predictions to be made, some of which have biological significance and which were later validated experimentally. Specifically, transcriptomic data analysis revealed that both infected and uninfected Kupffer cells are equally capable of responding to infection in a similar manner, something which wasn't previously evident in the literature. Using this transcriptomic data, I investigated through simulation, several experimental scenarios and elucidated a novel mechanism of immune system regulation in the liver microenvironment. Using an experimental model of Leishmania donovani infection, I demonstrated that such an immune regulatory mechanism can be overcome with the expansion of early promoter cells called Natural Killer T cells

LIPIcs, Volume 277, GIScience 2023, Complete Volume

LIPIcs, Volume 277, GIScience 2023, Complete Volum