Keywords
Records with Keyword: Dynamic Modelling
Modeling the Dynamics of Human Liver Failure Post Liver Resection
Babita K. Verma, Pushpavanam Subramaniam, Rajanikanth Vadigepalli
August 28, 2018 (v1)
Keywords: cell death, Dynamic Modelling, liver failure, liver regeneration, liver resection, virtual patient
Liver resection is an important clinical intervention to treat liver disease. Following liver resection, patients exhibit a wide range of outcomes including normal recovery, suppressed recovery, or liver failure, depending on the regenerative capacity of the remnant liver. The objective of this work is to study the distinct patient outcomes post hepatectomy and determine the processes that are accountable for liver failure. Our model based approach shows that cell death is one of the important processes but not the sole controlling process responsible for liver failure. Additionally, our simulations showed wide variation in the timescale of liver failure that is consistent with the clinically observed timescales of post hepatectomy liver failure scenarios. Liver failure can take place either instantaneously or after a certain delay. We analyzed a virtual patient cohort and concluded that remnant liver fraction is a key regulator of the timescale of liver failure, with higher remnant li... [more]
Dynamic modeling of the integrated methane reforming and nuclear heat systems
Leila Hoseinzade, Thomas A Adams II
August 15, 2018 (v1)
Keywords: Carbonless Heat, Dynamic Modelling, Methane Reforming, Process integration
In this study, a dynamic and two-dimensional model for a steam methane reforming process integrated with nuclear heat production was developed. The model is based on first principals and considers the conservation of mass, momentum and energy within the system. Very few model parameter needed to be fit based on the experimental data reported in the literature. Using the fitted model and existing data, an industrial scale design for the integrated steam reforming and nuclear heat process is proposed. The system performance was analyzed by studying the dynamic behaviour of the key variables of the system. It has been shown that the methane conversion in the SMR tubes are generally lower than conventional reforming processes due to the low temperature of the gas flows in the shell side. Several options were investigated to increase the conversion of the methane in the SMR tubes, we found that combining steam reforming with dry reforming processes together can provide significant improveme... [more]
Modeling and Optimal Design of Absorbent Enhanced Ammonia Synthesis
Matthew J. Palys, Alon McCormick, E. L. Cussler, Prodromos Daoutidis
July 31, 2018 (v1)
Keywords: ammonia synthesis, design optimization, Dynamic Modelling
Synthetic ammonia produced from fossil fuels is essential for agriculture. However, the emissions-intensive nature of the Haber⁻Bosch process, as well as a depleting supply of these fossil fuels have motivated the production of ammonia using renewable sources of energy. Small-scale, distributed processes may better enable the use of renewables, but also result in a loss of economies of scale, so the high capital cost of the Haber⁻Bosch process may inhibit this paradigm shift. A process that operates at lower pressure and uses absorption rather than condensation to remove ammonia from unreacted nitrogen and hydrogen has been proposed as an alternative. In this work, a dynamic model of this absorbent-enhanced process is proposed and implemented in gPROMS ModelBuilder. This dynamic model is used to determine optimal designs of this process that minimize the 20-year net present cost at small scales of 100 kg/h to 10,000 kg/h when powered by wind energy. The capital cost of this process sca... [more]
A Dynamic Optimization Model for Designing Open-Channel Raceway Ponds for Batch Production of Algal Biomass
Soumya Yadala, Selen Cremaschi
July 30, 2018 (v1)
Keywords: algae cultivation, batch production, Dynamic Modelling, harvest period, mathematical programming, parameter optimization, raceway pond design
This work focuses on designing the optimum raceway pond by considering the effects of sunlight availability, temperature fluctuations, and harvest time on algae growth, and introduces a dynamic programing model to do so. Culture properties such as biomass productivity, growth rate, and concentration, and physical properties, such as average velocity, pond temperature, and rate of evaporation, were estimated daily depending on the dynamic behavior of solar zenith angle, diurnal pattern of solar irradiance, and temperature fluctuations at the location. Case studies consider two algae species (Phaeodactylum. tricornutum and Isochrysis. galbana) and four locations (Tulsa, USA; Hyderabad, India; Cape Town, South Africa; and Rio de Janeiro, Brazil). They investigate the influences of the type of algae strain and geographical location on algae biomass production costs. From our case studies, the combination of I. galbana species grown in Hyderabad, India, with a raceway pond geometry of 30 cm... [more]
Modeling and simulation of an integrated steam reforming and nuclear heat system
Leila Hoseinzade, Thomas A. Adams II
June 12, 2018 (v1)
Keywords: Dynamic Modelling, Integrated Systems, Methane Reforming, Nuclear Heat, Simulation, Syngas
In this study, a dynamic and two-dimensional model for a steam methane reforming process integrated with nuclear heat production is developed. The model is based on first principles and considers the conservation of mass, momentum and energy within the system. The model is multi-scale, considering both bulk gas effects as well as spatial differences within the catalyst particles. Very few model parameters need to be fit based on the design specifications reported in the literature. The resulting model fits the reported design conditions of two separate pilot-scale studies (ranging from 0.4 to 10 MW heat transfer duty). A sensitivity analysis indicated that disturbances in the helium feed conditions significantly affect the system, but the overall system performance only changes slightly even for the large changes in the value of the most uncertain parameters.
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