http://hdl.handle.net/1721.1/7798 2013-05-24T07:12:53Z http://hdl.handle.net/1721.1/78811 The need for private sector-public sector collaborative planning in Singapore Ng, Philip C. T. (Philip Chee Tat) Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning and (M.S.)--Massachusetts Institute of Technology, Dept. of Civil Engineering, 1985.; MICROFICHE COPY AVAILABLE IN ARCHIVES, ROTCH AND ENGINEERING.; Bibliography: leaves 114-116. 1985-01-01T00:00:00Z http://hdl.handle.net/1721.1/78541 Incorporating uncertainty in the Life Cycle Cost Analysis of pavements Swei, Omar Abdullah Life Cycle Cost Analysis (LCCA) is an important tool to evaluate the economic performance of alternative investments for a given project. It considers the total cost to construct, maintain, and operate a pavement over its expected life-time. Inevitably, input parameters in an LCCA are subject to a high level of uncertainty, both in the short-term and long-term. Under its current implementation in the field, however, LCCA inputs are treated as static, deterministic values. Conducting such an analysis, although computationally simpler, hides the underlying uncertainty of the inputs by only considering a few possible permutations. This suggests that although computationally simpler, the answer from the analysis may not necessarily be the correct one. One methodology to account for uncertainty is to treat input parameters as probabilistic values, allowing the analysis to consider a range of possible outcomes. There are two major reasons as to why probabilistic LCCAs, although recommended, have not been streamlined into practice. First, the LCCA of construction projects is a large-scale problem with many input parameters with a high-level of uncertainty. Second, there is a significant gap in research that statistically quantifies uncertainty for input values. This research addresses the latter point by statistically quantifying four types of uncertainty: the unit cost of construction, quantity of material inputs, occurrence of maintenance activities, and a particular emphasis is placed upon characterizing the evolution of material prices over time. Having statistically characterized uncertainty in the LCCA analysis, the application of the probabilistically derived inputs is illustrated in three scenarios. Pavement alternative designs are derived for a set of traffic conditions in a given location. The results of the analysis indicate the integration of probabilistic input parameters in the LCCA process allows for more robust conclusions when evaluating alternative pavement designs. Additionally, the case study shows treating input parameters probabilistically could potentially alter the pavement selection, and one parameter that greatly influences this is material-specific price projections. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, 2012.; Cataloged from PDF version of thesis.; Includes bibliographical references (p. 81-87). 2012-01-01T00:00:00Z http://hdl.handle.net/1721.1/78524 Control systems for the building design process. Roth, Dennis Levin Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Civil Engineering; and, (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1975.; Bibliography: leaves 80-81. 1975-01-01T00:00:00Z http://hdl.handle.net/1721.1/78508 Evaluation of probabilistic underspecification as a method for incorporating uncertainty into comparative life cycle assessments Wildnauer, Margaret T. (Margaret Thea) Life cycle assessments are quickly becoming a crucial method through which the environmental impacts of products or processes are evaluated. A concern with current practice, however, is that the use of deterministic values for inputs and final results only represent a single scenario, not all possible values and outcomes, or even a real-world situation. By incorporating uncertainty, an LCA can account for inherent variation and the use of proxy data, both of which are common occurrences in LCA implementation. In a comparative LCA, this uncertainty allows a decision to be made between alternatives with a certain level of confidence. While uncertainty is necessary for credible results, its implementation can also be time consuming. As LCAs grow more common, methods of streamlining are being explored to reduce both the effort and cost. One such streamlining method that also incorporates uncertainty is probabilistic underspecification. This method evaluates environmental parameters by dividing them into different material and process categories. The lowest level of specification, Level 1, is defined by the type of material or process, such as metal or freight transportation. This category is then subdivided based on different characteristics of the material or process. The highest level of specification, Level 5, consists of the individual database processes used by traditional LCAs. This thesis compares the streamlining method of probabilistic underspecification to the more common method of incorporating uncertainty, termed here as individual probabilistic specification. A case study on alternative pavement designs is used to demonstrate and compare both the methodologies. The effort required for each methodology is compared by the percentage of processes specified at Level 5, which is 100% for individual probabilistic specification, but much less for probabilistic underspecification. The results of the case study showed that as little as 32% or less of the processes need to be specified at Level 5 in order to have the required level of confidence in the decision being made. It can be seen that, as a streamlining method to estimate the results of comparative LCAs, probabilistic underspecification is a viable option. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.; Cataloged from PDF version of thesis.; Includes bibliographical references (p. 97-100). 2012-01-01T00:00:00Z