92 research outputs found
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Equation-oriented modeling, simulation, and optimization of integrated and intensified process and energy systems
Process intensification, defined as unconventional design and/or operation of processes that results in substantial performance improvements, represents a promising route toward reducing capital and operating expenses in the chemical/petrochemical process industry, while simultaneously achieving improved safety and environmental performance. In this dissertation, intensification is approached from three different angles: reactor design and control, process flowsheet design and optimization, and production scheduling and control. In the first part of the dissertation, three novel concepts for improving the controllability of intensified microchannel reactors are introduced. The first concept is a latent energy storage-based temperature controller, where a phase change material is confined within the walls of an autothermal reactor to improve local temperature control. The second concept is a segmented catalyst layer which modulates the rate of heat generation and consumption along the length of an autothermal reactor. Finally, the third concept is a thermally actuated valve, which uses small-scale bimetallic strips to modulate flow in a microchannel reactor in response to temperature changes. The second part of the dissertation introduces a novel framework for equation-oriented flowsheet modeling, simulation and optimization. The framework consists of a pseudo-transient reformulation of the steady-state material and energy balance equations of process unit operations as differential-algebraic equation (DAE) systems that are statically equivalent to the original model. I show that these pseudo-transient models improve the convergence properties of equation-oriented process flowsheet simulations by expanding the convergence basin in comparison to conventional steady state equation-oriented simulators. A library of pseudo-transient unit operation models is developed, and several case studies are presented. Models for more complex unit operations such as a pseudo-transient multistream heat exchanger and a dividing-wall distillation column are later introduced, and can easily be included in the flowsheet optimization framework. In the final part of the dissertation, a paradigm for calculating the optimal production schedule in a fast changing market situation is introduced. This is accomplished by including a model of the dynamics of a process and its control system into production scheduling calculations. The scheduling-relevant dynamic models are constructed to be of lower order than a detailed dynamic process model, while capturing the closed-loop behavior of a set of scheduling-relevant variables. Additionally, a method is given for carrying out these production scheduling calculations online and in "closed scheduling loop,"' i.e., recalculating scheduling decisions upon the advent of scheduling-relevant process or market events. An air separation unit operating in a demand response scenario is used as a representative case study.Chemical Engineerin
Proceedings of the NASA Conference on Space Telerobotics, volume 2
These proceedings contain papers presented at the NASA Conference on Space Telerobotics held in Pasadena, January 31 to February 2, 1989. The theme of the Conference was man-machine collaboration in space. The Conference provided a forum for researchers and engineers to exchange ideas on the research and development required for application of telerobotics technology to the space systems planned for the 1990s and beyond. The Conference: (1) provided a view of current NASA telerobotic research and development; (2) stimulated technical exchange on man-machine systems, manipulator control, machine sensing, machine intelligence, concurrent computation, and system architectures; and (3) identified important unsolved problems of current interest which can be dealt with by future research
Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed into an algebraically simple form, which allows for computationally efficient algorithms. Three problem settings are discussed in this thesis: (1) filtering with Gaussians only, (2) Gaussian mixture filtering for strong nonlinearities, (3) Gaussian process filtering for purely data-driven scenarios. For each setting, efficient algorithms are derived and applied to real-world problems
Numerical and Analytical Methods in Electromagnetics
Like all branches of physics and engineering, electromagnetics relies on mathematical methods for modeling, simulation, and design procedures in all of its aspects (radiation, propagation, scattering, imaging, etc.). Originally, rigorous analytical techniques were the only machinery available to produce any useful results. In the 1960s and 1970s, emphasis was placed on asymptotic techniques, which produced approximations of the fields for very high frequencies when closed-form solutions were not feasible. Later, when computers demonstrated explosive progress, numerical techniques were utilized to develop approximate results of controllable accuracy for arbitrary geometries. In this Special Issue, the most recent advances in the aforementioned approaches are presented to illustrate the state-of-the-art mathematical techniques in electromagnetics
New Directions for Contact Integrators
Contact integrators are a family of geometric numerical schemes which
guarantee the conservation of the contact structure. In this work we review the
construction of both the variational and Hamiltonian versions of these methods.
We illustrate some of the advantages of geometric integration in the
dissipative setting by focusing on models inspired by recent studies in
celestial mechanics and cosmology.Comment: To appear as Chapter 24 in GSI 2021, Springer LNCS 1282
Sequential quadratic programming with indefinite Hessian approximations for nonlinear optimum experimental design for parameter estimation in differential–algebraic equations
In this thesis we develop algorithms for the numerical solution of problems from nonlinear
optimum experimental design (OED) for parameter estimation in differential–algebraic
equations. These OED problems can be formulated as special types of path- and control-
constrained optimal control (OC) problems. The objective is to minimize a functional on
the covariance matrix of the model parameters that is given by first-order sensitivities of the
model equations. Additionally, the objective is nonlinearly coupled in time, which make
OED problems a challenging class of OC problems. For their numerical solution, we propose
a direct multiple shooting parameterization to obtain a structured nonlinear programming
problem (NLP). An augmented system of nominal and variational states for the model
sensitivities is parameterized on multiple shooting intervals and the objective is decoupled
by means of additional variables and constraints. In the resulting NLP, we identify several
structures that allow to evaluate derivatives at greatly reduced costs compared to a standard
OC formulation.
For the solution of the block-structured NLPs, we develop a new sequential quadratic
programming (SQP) method. Therein, partitioned quasi-Newton updates are used to approximate the block-diagonal Hessian of the Lagrangian. We analyze a model problem with
indefinite, block-diagonal Hessian and prove that positive definite approximations of the
individual blocks prevent superlinear convergence. For an OED model problem, we show
that more and more negative eigenvalues appear in the Hessian as the multiple shooting grid
is refined and confirm the detrimental impact of positive definite Hessian approximations.
Hence, we propose indefinite SR1 updates to guarantee fast local convergence. We develop
a filter line search globalization strategy that accepts indefinite Hessians based on a new
criterion derived from the proof of global convergence. BFGS updates with a scaling strategy to prevent large eigenvalues are used as fallback if the SR1 update does not promote
convergence. For the solution of the arising sparse and nonconvex quadratic subproblems, a
parametric active set method with inertia control within a Schur complement approach is
developed. It employs a symmetric, indefinite LBL T -factorization for the large, sparse KKT
matrix and maintains and updates QR-factors of a small and dense Schur complement.
The new methods are complemented by two C++ implementations: muse transforms an
OED or OC problem instance to a structured NLP by means of direct multiple shooting.
A special feature is that fully independent grids for controls, states, path constraints, and
measurements are maintained. This provides higher flexibility to adapt the NLP formulation
to the characteristics of the problem at hand and facilitates comparison of different formulations in the light of the lifted Newton method. The software package blockSQP is an
implementation of the new SQP method that uses a newly developed variant of the quadratic
programming solver qpOASES. Numerical results are presented for a benchmark collection of
OED and OC problems that show how SR1 approximations improve local convergence over
BFGS. The new method is then applied to two challenging OED applications from chemical
engineering. Its performance compares favorably to an available existing implementation
Numerical and Evolutionary Optimization 2020
This book was established after the 8th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications
Space station systems: A bibliography with indexes (supplement 9)
This bibliography lists 1,313 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1, 1989 and June 30, 1989. Its purpose is to provide helpful information to researchers, designers and managers engaged in Space Station technology development and mission design. Coverage includes documents that define major systems and subsystems related to structures and dynamic control, electronics and power supplies, propulsion, and payload integration. In addition, orbital construction methods, servicing and support requirements, procedures and operations, and missions for the current and future Space Station are included
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