Dynamics and control of vapor recompression distillation

Vapor recompression distillation is an energy integrated distillation configuration which works on the principle of a heat pump. The tight material and energy integration in such columns shows a potential for intricate dynamics. In this paper, a systematic modeling framework is developed which explicitly captures the discrepancies between different material and energy flows present in such columns. This feature is documented to lead to stiff dynamic equations and multiple time-scale dynamics. Through a nested application of singular perturbations, reduced order non-stiff models are derived which capture the dynamics in each time-scale. A hierarchical control strategy is then proposed exploiting this time-scale multiplicity. A case of propane–propylene separation is considered to illustrate these results and demonstrate the effectiveness of the proposed control strategy via a simulation case study.     

Model reduction of multi-scale chemical Langevin equations

This paper addresses the model reduction problem for a class of stiff chemical Langevin equations that arise as models of biomolecular networks with fast and slow reactions and can be described as continuous Markov processes. Initially, a coordinate transformation is sought that allows the decoupling of fast and slow variables in the model equations. Necessary and sufficient conditions are derived for such a linear transformation to exist, along with an explicit change of variables which achieves the desired decoupling. For the systems for which this step is applicable, the method of adiabatic elimination is applied to determine a representation of the slow dynamics. Theoretical concepts and results are illustrated with simple examples.     

Modeling,optimization, and cost analysis of an IGCC plant with a membrane reactor for carbon capture

This article presents a theoretical study on the integration of a membrane reactor (MR) for carbon capture into an integrated gasification combined cycle (IGCC) plant. First‐principles, simplified systems‐level models for the individual IGCC units and the MR are introduced for their subsequent plantwide integration. The integrated plant model is then used for simulation studies that assume different MR characteristics. Using this model, an optimization problem is formulated to analyze the MR effects when adding it to the IGCC plant, while satisfying all of the process constraints in streams and performance variables. The solution of this optimization problem indicates improvements in the original case studies, including capital cost savings as high as $18 million for the optimal case under nominal process conditions. To determine the cost implications of inserting the MR into the IGCC plant, a differential cost analysis is performed taking into account major plant capital and operating costs. This analysis considers the same amount of coal and power generation for cases with and without the MR. The results of this analysis based on a present value of annuity calculation show break even costs for the MR within the feasible range for membrane fabrication, even for short membrane lifetimes. © 2016 American Institute of Chemical Engineers AIChE J, 62: 1568–1580, 2016     

A framework for ammonia supply chain optimization incorporating conventional and renewable generation

Ammonia is an essential nutrient for global food production brought to farmers by a well‐established supply chain. This article introduces a supply chain optimization framework which incorporates new renewable ammonia plants into the conventional ammonia supply chain. Both economic and environmental objectives are considered. The framework is then applied to two separate case studies analyzing the supply chains of Minnesota and Iowa, respectively. The base case results present an expected trade‐off between cost, which favors purchasing ammonia from conventional plants, and emissions, which favor building distributed renewable ammonia plants. Further analysis of this trade‐off shows that a carbon tax above $25/t will reduce emissions in the optimal supply chain through building large renewable plants. The importance of scale is emphasized through a Monte Carlo sensitivity analysis, as the largest scale renewable plants are selected most often in the optimal supply chain. © 2017 American Institute of Chemical Engineers AIChE J, 63: 4390–4402, 2017     

Seismic displacements of landfills and deformation of geosynthetics due to base sliding

Seismic design of waste landfills has been a subject of intense research over the past two decades, primarily due to the severe environmental impact of a potential failure. The majority of the related studies have been focused on the stability assessment of landfills utilizing permanent deformation methods. However, previous investigations have not fully addressed the impact of the composite liner system on the seismic performance of the geostructure, mainly expressed as potential sliding development, which is greatly affected by the geometry and the resulting initial static stress state of the landfill. Therefore, the aforementioned issues are investigated via a detailed parametric study, where the dynamic behaviour of the composite liner system is examined both analytically and numerically. The conducted coupled analyses indicated that the most significant parameters of the complex dynamic response of waste landfills can be reduced in two ratios that comprise functions of the main characteristics of the geostructure and of the excitation. Moreover, two distinct failure patterns have been identified with respect to the characteristics of the distribution of the permanent displacements along the interface and the axial deformation along the geosynthetic. The occurrence conditions of these failure patterns can be determined in terms of the two abovementioned ratios as verified by the analytical results of the critical acceleration of a simple SDOF system.     

A low-cost Mr compatible ergometer to assess post-exercise phosphocreatine recovery kinetics

Objective

To develop a low-cost pedal ergometer compatible with ultrahigh (7 T) field MR systems to reliably quantify metabolic parameters in human lower leg muscle using phosphorus magnetic resonance spectroscopy.

Materials and methods

We constructed an MR compatible ergometer using commercially available materials and elastic bands that provide resistance to movement. We recruited ten healthy subjects (eight men and two women, mean age ± standard deviation: 32.8 ± 6.0 years, BMI: 24.1 ± 3.9 kg/m²). All subjects were scanned on a 7 T whole-body magnet. Each subject was scanned on two visits and performed a 90 s plantar flexion exercise at 40% maximum voluntary contraction during each scan. During the first visit, each subject performed the exercise twice in order for us to estimate the intra-exam repeatability, and once during the second visit in order to estimate the inter-exam repeatability of the time constant of phosphocreatine recovery kinetics. We assessed the intra and inter-exam reliability in terms of the within-subject coefficient of variation (CV).

Results

We acquired reliable measurements of PCr recovery kinetics with an intra- and inter-exam CV of 7.9% and 5.7%, respectively.

Conclusion

We constructed a low-cost pedal ergometer compatible with ultrahigh (7 T) field MR systems, which allowed us to quantify reliably PCr recovery kinetics in lower leg muscle using ³¹P-MRS.

     

Requirements capture and analysis: A survey of current practice

This paper presents the findings of a detailed survey of 107 projects in which the iterative nature of requirements analysis was explored in economic terms. The survey was conducted from the point of view of the project manager. The results indicate that half of the projects take three or more interations to complete the requirements, that the use of methodologies and project characteristics affect the number of iterations, and that in half of the projects the number of iterations planned was different from the number actually carried out. The paper concludes by attempting to explain the relationship between the economics of the requirements process and the number of iterations through a spiral model of requirements capture and analysis.     

Scheduling-informed optimal design of systems with time-varying operation: A wind-powered ammonia case study

The time-varying operation of chemical plants offers economic advantages, particularly in the presence of time-sensitive electricity markets and renewable energy generation. However, the uncertainty and short-timescale variability associated with renewable energy production, as well as the nonconvex process and cost models typically associated with chemical processes, make finding the optimal design of such systems challenging. In this work, a new approach is presented to finding the optimal design of systems with time-varying operation, called scheduling-informed design, whereby the optimal operation of many designs is determined and the resulting cost correlations into the optimal design problem are embedded. This method is applied to a case study of wind-powered ammonia generation and showed that it greatly improves the computational tractability of the optimal design problem and predicts with greater accuracy operating costs realized because of uncertainty in forecasting. © 2018 American Institute of Chemical Engineers AIChE J, 65: e16434 2019