About the Numerical Methods in Civil Engineering Journal

Editorial message:
Natural and man-made crises in the world have become distressingly familiar features of the globalised world and God’s creation. Often, the crises are complex in nature, global in scale, and are the result of multiple, unanticipated, inter-related events of spatial and temporal dimensions. Scientists are strongly motivated to understand and anticipate the crises to mitigate their effects and recover from their consequences. To conquer, governments anchor to several tools the most important of which being science and technology. Science targets detecting potential features of the creatures and providing the ground to employ their capabilities. Our moral obligation is to generate possibilities, to discover the infinite while complex and multi-dimension ways, to play in their games, and eventually, rationalize and justify the future of human life interactions upon the best of the existing knowledge. It will take all possible species of intelligence in order for the universe to understand itself. Science, in this sense, is holy; it makes a divine trip. In the meanwhile, the term numerical analysis, as a drive, is too restrictive, failing to capture the intellectual breadth required for modern computational scientists to anticipate future upon the existing knowledge. In reality, although numerical analysis remains as a useful label for an established body of knowledge, the scientists’ consensus is that the age in which a researcher spends a career within the narrow confines of such body of knowledge – if it ever existed – has long passed. To move the field forward and to advance in algorithms, analysis and modeling, we must develop our understanding in both pure mathematics and applications.
 
Several ideas have been explored towards the growth of numerical analysis over the past forty years, as one may measure them by watching the impact factors and counting the pages in the relevant journals. After discussing the merits of such metrics, the utilities can be gauged and scaled by the extent to which our algorithms and software are applied, even if eventual users are unaware of the ideas upon which they rely. This may be considered as a real impact. Contemporary problems specifically in civil engineering incorporate more sophisticated physical models, and even these are typically only objective functions for a design optimization that is the true goal of the computation. Models developed by engineers and scientists appear more and more extreme while current methods sound completely inadequate for such models. Conceptually, it may be emphasized that the future of the discipline can only go well if there is more realization and mathematics is used correctly in numerical models. In addition, the role that quantifying uncertainty now plays in computational science is receiving an increased attention. No longer is it sufficient to compute a "best guess" for a solution; the result must now be qualified as "to how confident the researcher is in that best guess." In the forthcoming years, we will see growing use of several numerical algorithms as weak and strong forms on discrete models, networks, Monte Carlo simulation and databases. The conditions may promote the idea of the conformation of real cases with "mathematical sciences" as a whole and with a relaxation of the borders that separate the field from statistics and operational research.
 
In addition to changes in mathematical tools and applications, it is emphasized that numerical analysts must anticipate the significant changes in computer architecture on the horizon and be ready with appropriate algorithms to match. Real changes come from algorithms rather than faster processors. Developments of numerical methods followed by science will continue to surprise us with what they discover and create; then it will again astound us by devising other novel methods. At the core of science's self modification is technology. New tools enable the structures of knowledge and the ways of discovery. Whereas the achievement of science is to know new things, the evolution of science is to know them in new ways. What evolves is less related to the body of what we know but more to the nature of our knowing. The two branches, science and numerical analysis, are the foundations for our subjective level of culture and society. While civilizations appear and disappear, science grows steadily onwards. In other words, recursion is the essence of science; science papers cite other each other, and that process of research, pointing at itself, invokes higher levels, forming the emergent shape of the citation space. Recursion always does that. It is the engine of scientific progress and, thus, of the progress of society.

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