Optimization of Mechanical Supports for Large Superconductive Magnets

Hilal, M. Abu; Boom, R.

doi:10.1007/978-1-4613-9850-9_24

Cited by 18 publications

(16 citation statements)

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“…In this section, we reformulate the Kokkolaras et al model (as extended from that of [22]) to include constraints on thermal expansion, stress, and mass. Much of this discussion comes directly from the presentation in [26], although some of the discussion of stress is similar to that of [23].…”

Section: Basic Model Of Thermal Insulation Systemsmentioning

confidence: 99%

“…The software and function files were validated by mimicking the designs of [22] and [23], running these problems, and comparing the designs. In both of these previous papers, the authors applied their optimizer to cases of 1-3 heat intercepts with insulators made of either 304 stainless steel or plane-cloth fiberglass epoxy.…”

Section: Validationmentioning

confidence: 99%

“…Hilal and Boom [22] used a gradient-based optimizer to minimize power for n = 1, 2, and 3 intercepts with two choices of insulators of constant cross-sectional area, but without mixing insulator types within the system. Hilal and Eyssa [23] studied the same problem, but with variable cross sectional area for the mechanical supports.…”

Section: Introductionmentioning

confidence: 99%

“…This required an extension of the theory [7] to be able to deal with categorical variables. They achieved a 65% reduction in required refrigeration power from that of [22] by using the Audet-Dennis mixed variable generalized pattern search (MGPS) algorithm [7] to solve this bound constrained mixed variable programming (MVP) problem. However, other than choosing the specific list of possible insulators, they did not consider certain load-bearing aspects of the problem, such as thermal expansion, system mass, and stress, because these are modelled as nonlinear constraints.…”

Section: Introductionmentioning

confidence: 99%

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Mixed Variable Optimization of a Load-Bearing Thermal Insulation System Using a Filter Pattern Search Algorithm

Abramson

2004

Optimization and Engineering

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This paper describes the optimization of a load-bearing thermal insulation system characterized by hot and cold surfaces with a series of heat intercepts and insulators between them. The optimization problem is represented as a mixed variable programming (MVP) problem with nonlinear constraints, in which the objective is to minimize the power required to maintain the heat intercepts at fixed temperatures so that one surface is kept sufficiently cold. MVP problems are more general than mixed integer nonlinear programming (MINLP) problems in that the discrete variables are categorical; i.e., they must always take on values from a predefined enumerable set or list. Thus, traditional approaches that use branch and bound techniques cannot be applied.In a previous paper, a linearly constrained version of this problem was solved numerically using the Audet-Dennis generalized pattern search (GPS) method for MVP problems. However, this algorithm may not work for problems with general nonlinear constraints. A new algorithm that extends that of Audet and Dennis by incorporating a filter to handle nonlinear constraints makes it possible to solve the more general problem. Additional nonlinear constraints on stress, 2 mass, and thermal contraction are added to that of the previous work in an effort to find a more realistic feasible design. Several computational experiments show a substantial improvement in power required to maintain the system, as compared to the previous literature. The addition of the new constraints leads to a very different design without significantly changing the power required. The results demonstrate that the new algorithm can be applied to a very broad class of optimization problems, for which no previous algorithm with provable convergence results could be applied. Report Documentation Page

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Section: Basic Model Of Thermal Insulation Systemsmentioning

confidence: 99%

Section: Validationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mixed Variable Optimization of a Load-Bearing Thermal Insulation System Using a Filter Pattern Search Algorithm

Abramson

2004

Optimization and Engineering

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“…Bejan (1977) introduced the concept of designing heat exchangers for specified irreversibility rather than specified amount of heat transferred. Many authors used this technique in the field of cryogenic engineering Smith (1974, 1976), Bejan (1975), and Hilal and Boom (1976)). …”

Section: Introductionmentioning

confidence: 99%