Increasing profit by improving gas handling systems

The availability of a smelter’s gas handling systems is crucial to the profitability of the plant. In new projects, the best technical and economic result is achieved if the gas handling systems are integrated into the process. This integration requires close cooperation between the smelter process designer and the gas handling designer. In modernization projects, environmentally, economically, and technically feasible solutions can be found, and smelter productivity can be increased when imagination and new technology are applied.     

A logarithmic complexity divide-and-conquer algorithm for multi-flexible-body dynamics including large deformations

A new algorithm is presented for the modeling and simulation of multi-flexible-body systems. This algorithm is built upon a divide-and-conquer-based multibody dynamics framework, and it is capable of handling arbitrary large rotations and deformations in articulated flexible bodies. As such, this work extends the current capabilities of the flexible divide-and-conquer algorithm (Mukherjee and Anderson in Comput. Nonlinear Dyn. 2(1):10–21, 2007), which is limited to the use of assumed modes in a floating frame of reference configuration. The present algorithm utilizes the existing finite element modeling techniques to construct the equations of motion at the element level, as well as at the body level. It is demonstrated that these equations can be assembled and solved using a divide-and-conquer type methodology. In this respect, the new algorithm is applied using the absolute nodal coordinate formulation (ANCF) (Shabana, 1996). The ANCF is selected because of its straightforward implementation and effectiveness in modeling large deformations. It is demonstrated that the present algorithm provides an efficient and robust method for modeling multi-flexible-body systems that employ highly deformable bodies. The new algorithm is tested using three example systems employing deformable bodies in two and three spatial dimensions. The current examples are limited to the ANCF line or cable elements, but the approach may be extended to higher order elements. In its basic form, the divide-and-conquer algorithm is time and processor optimal, yielding logarithmic complexity O(log(N _b )) when implemented using O(N _b ) processors, where N _b is the number of bodies in the system.     

A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem

Meta-heuristics are frequently used to tackle NP-hard combinatorial optimization problems. With this paper we contribute to the understanding of the success of 2-opt based local search algorithms for solving the traveling salesperson problem (TSP). Although 2-opt is widely used in practice, it is hard to understand its success from a theoretical perspective. We take a statistical approach and examine the features of TSP instances that make the problem either hard or easy to solve. As a measure of problem difficulty for 2-opt we use the approximation ratio that it achieves on a given instance. Our investigations point out important features that make TSP instances hard or easy to be approximated by 2-opt.     

An extended divide-and-conquer algorithm for a generalized class of multibody constraints

An extension to the divide-and-conquer algorithm (DCA) is presented in this paper to model constrained multibody systems. The constraints of interest are those applied to the system due to the inverse dynamics or control laws rather than the kinematically closed loops which have been studied in the literature. These imposed constraints are often expressed in terms of the generalized coordinates and speeds. A set of unknown generalized constraint forces must be considered in the equations of motion to enforce these algebraic constraints. In this paper dynamics of this class of multibody constrained systems is formulated using a Generalized-DCA. In this scheme, introducing dynamically equivalent forcing systems, each generalized constraint force is replaced by its dynamically equivalent spatial constraint force applied from the appropriate parent body to the associated child body at the connecting joint without violating the dynamics of the original system. The handle equations of motion are then formulated considering these dynamically equivalent spatial constraint forces. These equations in the GDCA scheme are used in the assembly and disassembly processes to solve for the states of the system, as well as the generalized constraint forces and/or Lagrange multipliers.     

Are My Neighbours Ageing Yet? Local Dimensions of Demographic Change in German Cities

Among the highly developed countries, demographic ageing is particularly advanced in Germany. Accentuated by migration, there is great regional variation in the progress of demographic change. Within urban areas, residential neighbourhoods differ considerably in their demographic composition and perspectives. Based on municipal data, this paper examines regional variability in the diversity and pace of neighbourhood-level ageing. Focusing on the Rhine-Ruhr conurbation in North Rhine-Westphalia, the analysis outlines at what pace ageing proceeds in a variety of neighbourhoods, which attract no constant influx of working-age migrants. After decades of suburbanisation, in the period from 1998 to 2008 regional migration concentrated on the central districts of large cities. More profoundly in the most prosperous cities growing in population than in other cities, childless working-age adults separate from other age groups and family types in selected central city quarters. The findings suggest that spatial differentials in ageing are likely to affect future location decisions and, thereby, regional and local prosperity.     

Expected runtimes of evolutionary algorithms for the Eulerian cycle problem

Evolutionary algorithms are randomized search heuristics, which are applied to problems whose structure is not well understood, as well as to problems in combinatorial optimization. They have successfully been applied to different kinds of arc routing problems. To start the analysis of evolutionary algorithms with respect to the expected optimization time on these problems, we consider the Eulerian cycle problem. We show that a variant of the well-known (1+1)$(1+1)$ EA working on the important encoding of permutations is able to find an Eulerian tour of an Eulerian graph in expected polynomial time. Altering the operator used for mutation in the considered algorithm, the expected optimization time changes from polynomial to exponential.