1,720,973 research outputs found
Rule Input Network Generator
No full textRING is an automated reaction network generation and analysis tool that outputs reaction networks for complex reactive systems from user-defined inputs of initial reactants and chemical reaction rules. RING also takes user-provided post-processing instructions to analyze the topology of the generated network; possible post-processing instructions include: reaction pathway queries to isolate routes from defined reactants to products, lumping instructions to group functionally equivalent species (e.g. isomers) for network reduction, and mechanism queries to establish sequences of elementary steps describing the overall transformations of reactants to products.Initiative for Renewable Energy at the University of Minnesota, the National Science Foundation, and the U. S. Department of EnergyDaoutidis, Prodromos. (2018). Rule Input Network Generator. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/197603
Integrating operations and control: A perspective and roadmap for future research
No full textThis "white paper" is a concise perspective based on a session during FIPSE 3, held in Rhodes, Greece, June 20-23, 2016. This was the third conference in the series "Future Innovation in Process Systems Engineering" (http://fi-in-pse.org), which takes place every other year in Greece, witha limited number of participants and just three topics/sessions whose objective is to pose and discuss open research challenges in Process Systems Engineering. This specific session comprised invited talks by Sigurd Skogestad and Iiro Harjunkoski, followed by short presentations by the participants and extensive discussions. The paper does not intend to provide a comprehensive review on the subject, or a detailed exposition of the concepts and problems. Its aim is to highlight open problems and directions for future research. (c) 2018 Elsevier Ltd. All rights reserved.
Design of optimal alternative fuels and their production processes
No full textTo reduce emissions in the transport sector, renewable sustainable energy carriers and efficient propulsion technologies are needed. The associated raw material, process, fuel, and engine technology aspects line up to a fuel value chain that needs to be designed with respect to cost, resource, and emission efficiency. This thesis aims at optimizing the different aspects of the fuel value chain for cost and environmental criteria by using and advancing methods for an (integrated) process and fuel design. Starting with the choice of raw materials and processes, screening methods for bio based processes are advanced to make them applicable for other raw material resources and associated processing pathways. This enables production comparisons of bio- and electricity based fuel species regarding cost and environmental criteria. The analysis of optimized production processes shows that bio-based processes generally lead to lower overall costs due to lower raw material costs compared to electricity-based production. However, conversion of biomass is often associated to higher carbon losses and energy-intensive separations, whereas electricity-based production can be achieved with low material losses and often facile liquid-gas separations. Furthermore, feedstock combinations can result in synergies, e.g., by upgrading CO2 from bioethanol production with electricity-based H2. The results of the screening thus provide a first understanding of optimal application areas and possibilities for combining raw materials in renewable fuel production. One step further in the fuel value chain, optimization of production aspects does often not suffice to design a technically viable (multi-species) fuel. Instead, fuel requirements posed by the engine application must also be taken into account. To identify cost- and emission-optimal fuel production processes while ensuring fuel compositions feasible in an engine, a new method for simultaneous process and product design is developed. In contrast to previous integrated methods, this approach accounts for the energy requirement of the production processes and thus enables cost and emission optimization. The new method is demonstrated for the design of biofuels for ultra-high efficiency engines (UHEEs).Finally, the analysis is expanded to the last step of the fuel value chain, i.e., the use of the fuel in the engine. To this end, the fuel requirements are employed as the link between the integrated process/fuel design and the engine application to determine cost and emission optimized engine/fuel combinations. The analysis considers three types of spark-ignition engines, a variety of selective, renewable processing routes, and fossil gasoline that is provided as an additional blending option. By running the new integrated design problem separately for each of the three engine types, optimal fuel production designs and associated fuel compositions are determined that are suitable for the considered engine type. The comparison of these optimal engine/fuel combinations indicates that fuels for advanced engines, i.e., UHEEs and flexible fuel vehicle engines, show a better cost/emission Pareto performance than fuels for conventional engines, which advocates a future technological change away from today’s gasoline engines
Synthesis of feedforward/feedback control systems for nonlinear processes.
No full textIn this thesis, the unified problem of disturbance rejection and output tracking for general nonlinear processes is studied, using methods from differential geometry. An analysis framework is initially established, through a detailed study of the concept of relative order. The general problem of disturbance rejection and output tracking is formulated as a feedforward/feedback control problem, and is addressed first for single-input single-output processes and then for multiple-input multiple-output processes. Feedforward/state feedback laws are synthesized that completely eliminate the effect of measured disturbances on the controlled outputs and induce a well-characterized linear input/output behavior. A general feedforward/feedback control structure is developed that also accounts for modeling error and unmeasured disturbances. The developed control methodology is applied to composition control in a cascade of chemical reactors and to temperature and number average molecular weight control in a continuous polymerization reactor. On the basis of the properties of relative order and the controller synthesis results, the problem of synthesis of control configurations is also addressed. A general framework for the structural evaluation of alternative control configurations is developed, based on fundamental structural limitations in the control quality and structural coupling considerations. The developed evaluation framework is applied to the synthesis of control configurations in an evaporation unit, a continuous chemical reactor and a heat-exchanger network.PhDApplied SciencesChemical engineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/128744/2/9135582.pd
Synthesis of feedforward/state feedback controllers for nonlinear processes
Get PDFA systematic method for synthesizing feedforward/state feedback controllers for a broad class of SISO nonlinear systems with measurable disturbances is presented. Depending on the structural characteristics of the system, the control law can be static or dynamic. The closed-loop system is independent of the measurable disturbances and linear with respect to set point changes. The performance of the proposed control scheme is illustrated through an example of composition control in a system of three CSTR's in series.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/37404/1/690351004_ftp.pd
Nonlinear state feedback control of second-order nonminimum-phase nonlinear systems
Get PDFThe present work addresses the problem of synthesizing nonlinear state feedback controllers for second-order nonminimum-phase nonlinear systems. The concept of a first-order nonlinear all-pass is first introduced. A class of static state feedback control laws is then developed that makes the closed-loop system equivalent, under an appropriate coordinate transformation, to a nonlinear first-order all-pass in series with a linear first-order lag. A particular control law from this class is calculated that results in ISE-optimal response. The performance of the proposed methodology in set point tracking is evaluated through numerical simulations in a CSTR example.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28607/1/0000416.pd
Computationally efficient solution of mixed integer model predictive control problems via machine learning aided Benders Decomposition
Get PDFMixed integer Model Predictive Control (MPC) problems arise in the operation
of systems where discrete and continuous decisions must be taken simultaneously
to compensate for disturbances. The efficient solution of mixed integer MPC
problems requires the computationally efficient and robust online solution of
mixed integer optimization problems, which are generally difficult to solve. In
this paper, we propose a machine learning-based branch and check Generalized
Benders Decomposition algorithm for the efficient solution of such problems. We
use machine learning to approximate the effect of the complicating variables on
the subproblem by approximating the Benders cuts without solving the
subproblem, therefore, alleviating the need to solve the subproblem multiple
times. The proposed approach is applied to a mixed integer economic MPC case
study on the operation of chemical processes. We show that the proposed
algorithm always finds feasible solutions to the optimization problem, given
that the mixed integer MPC problem is feasible, and leads to a significant
reduction in solution time (up to 97% or 50x) while incurring small error (in
the order of 1%) compared to the application of standard and accelerated
Generalized Benders Decomposition
Inversion and zero dynamics in nonlinear multivariable control
Get PDFThis work concerns general multiple-input/multiple-output (MIMO) nonlinear systems with nonsingular characteristic matrix. For these systems, the problem of inversion is revisited and explicit formulas are derived for the full-order and the reduced inverse system. The reduced inverse naturally leads to an explicit calculation of the unforced zero dynamics of the system and the definition of a concept of forced zero dynamics. These concepts generalize the notion of transmission zeros for MIMO linear systems in a nonlinear setting. Chemical engineering examples are given to illustrate the calculation of zero dynamics. Input/output linearization is then interpreted as canceling the forced zero dynamics of the system, and precise internal stability conditions are derived for the closed-loop system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/37419/1/690370406_ftp.pd
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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