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Masters Theses in the Pure and Applied Sciences was first conceived, published, and disseminated by the Center for Information and Numerical Data Analysis and Synthesis (CINDAS)* at Purdue University in 1957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dis semination phases of the activity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the though that such an arrangement would be more beneficial to the academic and general scientific and technical community. After five years of this joint undertaking we had concluded that it was in the interest of all concerned if the printing and distribution of the volumes were handled by an international publishing house to assure improved service and broader dissemi nation. Hence, starting with Volume 18, Masters Theses in the Pure and Applied Sciences has been disseminated on a worldwide basis by Plenum Publishing Corporation of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 37 (thesis year 1992) a total of 12,549 thesis titles from 25 Canadian and 153 United States universities. We are sure that this broader base for these titles reported will greatly enhance the value of this impor tant annual reference work. While Volume 37 reports theses submitted in 1992, on occasion, certain uni versities do report theses submitted in previous years but not reported at the time.
This book is an outcome of the sixth conference on bearing capacity of roads and airfield held in Lisbon, Portugal. It covers the following topics: bearing capacity policies, concepts, costs and condition surveys; analysis and modelling; design and environmental effects; and asphalt mixtures.
This synthesis report will be of interest to pavement and geotechnical design and research engineers, geologists and engineering geologists, and related laboratory personnel. It describes the current practice for measuring in situ mechanical properties of pavement subgrade soils. The tests conducted to measure the mechanical properties of soil strength and stiffness are the primary topics, and these are discussed in the context of design procedures, factors affecting mechanical properties, and the variability of measurements. Information for the synthesis was collected by surveying U.S., Canadian, and selected European transportation agencies and by conducting a literature search. This TRB report provides information on existing and emerging technologies for static and dynamic, and destructive and nondestructive testing for measuring in situ mechanical properties of pavement subgrade soils. Correlations between in situ and laboratory tests are presented. The effects of existing layers on the measurement of subgrade properties, and soil spatial and seasonal variability are discussed. Most importantly, the use of soil properties in pavement design and evaluation are explained. New applications or improvements to existing test methods to support the use of mechanistic/stochastic-based pavement design procedures are also explained.
At head of title: National Cooperative Highway Research Program.
The term “soft computing” applies to variants of and combinations under the four broad categories of evolutionary computing, neural networks, fuzzy logic, and Bayesian statistics. Although each one has its separate strengths, the complem- tary nature of these techniques when used in combination (hybrid) makes them a powerful alternative for solving complex problems where conventional mat- matical methods fail. The use of intelligent and soft computing techniques in the field of geo- chanical and pavement engineering has steadily increased over the past decade owing to their ability to admit approximate reasoning, imprecision, uncertainty and partial truth. Since real-life infrastructure engineering decisions are made in ambiguous environments that require human expertise, the application of soft computing techniques has been an attractive option in pavement and geomecha- cal modeling. The objective of this carefully edited book is to highlight key recent advances made in the application of soft computing techniques in pavement and geo- chanical systems. Soft computing techniques discussed in this book include, but are not limited to: neural networks, evolutionary computing, swarm intelligence, probabilistic modeling, kernel machines, knowledge discovery and data mining, neuro-fuzzy systems and hybrid approaches. Highlighted application areas include infrastructure materials modeling, pavement analysis and design, rapid interpre- tion of nondestructive testing results, porous asphalt concrete distress modeling, model parameter identification, pavement engineering inversion problems, s- grade soils characterization, and backcalculation of pavement layer thickness and moduli.