User cost models are used in bridge management systems to quantify, in economic terms, the potential safety and mobility benefits of functional improvements to bridges. One component of many such models is a formula to predict traffic accident risk on the basis of bridge characteristics such as roadway width and approach roadway alignment. A critical analysis of the user cost model used in AASHTO’s Pontis and Bridgit systems found that the model was overly sensitive to extremes of roadway width, yielding unrealistically high benefit estimates. A new model was developed using Florida data on bridge characteristics and traffic accidents. The new model has superior behavior and statistical characteristics on a full inventory of state highway bridges. Since it relies solely on National Bridge Inventory data items, the model is readily transferable to many different bridge management systems.
Both South Florida and Qatar have unique needs and requirements for oil spill response, yet both have basic needs for a contingency plan for responding to oil spills. South Florida has a diverse coastal environment that is important not only for its ecosystem but for the revenue it generates from tourism and fishing. Qatar is sitting on the world’s largest natural gas fields and some larger oil fields and is one of the world’s richest countries. The oil spill response system of South Florida differs in operational structure from that of Qatar. South Florida’s response system is a network-based operation controlled by county or city officials, depending on the degree of the spill and availability of resources. Qatar’s system is a central control operation, with primary authority and control of any oil spill response assumed by the Qatar General Petroleum Corporation (QGPC). Local industries are expected to protect their own facilities, but QGPC also responds to those spills that threaten public and government coasts and the Persian Gulf ecosystem. The University of Florida has developed a computerized database for South Florida that enables officials of national, regional, and state response teams to quickly identify and deploy required equipment and personnel for an oil spill and to follow cleanup operations. The specific advantage of the South Florida system over the Qatar system is in the oil spill response information system database, which includes information on oil-sensitive shorelines, response teams, disposal sites, cleanup organizations, and equipment. Furthermore, the typical oil spill cleanup response times for selected contractors indicate the most efficient choice of contractor for possible oil spills at different locations.
A performance bond provides the assurance that an awarded construction project will be satisfactorily completed in the event that the contractor is unable to complete the project as agreed and the contract is terminated. First passed into U.S. law in the late 1800s, performance bonds protect against financial losses. The ability of contractors to provide a performance bond has mistakenly been assumed as a guarantee that contractors will perform well on the projects they are awarded. Indications are that there is a need to evaluate the benefits and the costs of using performance bonds. This paper examines the benefit–cost ratios of performance bonds on a national basis. Analysis was performed on state construction project data collected for contract awards from September 2007 to September 2009. The results of the analysis suggest that states with a small number of defaults, or none at all, did not benefit from having performance bonds, whereas those states with numerous defaults did benefit. In conclusion, the results suggest that performance bonds are beneficial to states that experience a large number of defaults.
He has received numerous awards including Fulbright cholarship awards, teaching awards, best paper awards, community service awards, and admission as an Eminent Engineer into Tau Beta Pi. His research on passive radon-resistant new residential building construction was adapted in HB1647 building code of Florida Legislature. Najafi is a member of numerous professional societies and has served on many committees and programs, and continuously attends and presents refereed papers at international, national, and local professional meetings and conferences. Lastly, Najafi attends courses, seminars and workshops, and has developed courses, videos and software packages during his career. His areas of specialization include transportation planning and management, legal aspects, construction contract administration, public works and renewable energy. Brine disposal and energy consumption for treatment are also discussed in the paper. The source water and brine disposal requirements for each method vary based on system efficiency. As a system's treatment efficiency increased, the source water requirement decreased and the salinity of the brine solution increased. RO was the least energy intensive treatment method, requiring 3-5.5 kWh/m 3 . MED and MVC had similar energy requirements at 6.5-12 kWh/m 3 . The least efficient treatment method was MSF, requiring 13.5-25.5 kWh/m 3 . High salinity and large energy requirements can be mitigated by pairing the desalination facility with a waste water treatment plant. Effluent can be mixed with the brine to reduce salinity and thermal energy can be supplied to reduce energy demand.
The United Slates lacks in the research and development of robots and construction automation. In comparison, construction companies in Japan take more aggressive stand in the research and development of this technology. This paper studies both Japan and US basic construction activities, research and development, social implications , automation technology, and construction robots economic feasibility. Construction robot productivity is always higher when materials are standardized, and repetition activities are involved. Improving productivity, reducing manpower, shortening construction time, reduction of costs, improving quality, improving work conditions, safety, and benefits to the environment are presented in this paper.
The purpose of this paper is to introduce the potential application of robotics in the field of construction. Recent applications of robotic technology have been explored in light of its economic viability. The decision to introduce a robot into the construction work place must be carefully analyzed since the potential cost of introduction goes far beyond the initial capital purchase. Some of the elements of robot costs include the capital cost, the costs of transportation, installation, operation and maintenance, insurance, staff training and awareness, etc. Other socio-economic concerns are also discussed. A justification for introducing robots in light of reduction in health hazards, increase in work productivity, labor cost savings is presented. There is a great potential for using robots in certain construction activities which will result in higher productivity. Furthermore, it is economical to use robots in a series of simple and repetitive work tasks.
What is the optimum acceptance sample size (n)? Recent research by Gharaibeh and colleagues found that when incoming lots are anticipated to be high quality, the optimum n is relatively small (n = 3 for many acceptance quality characteristics). The finding was received with some skepticism, and many questions were raised about the optimization model and underlying assumptions. This paper summarizes follow-up research that more closely examined the optimization model elements and assumptions in an attempt to confirm or refute the finding by Gharaibeh and colleagues. By using a somewhat modified model and assumptions based where possible on actual data, the conclusions reached by Gharaibeh and colleagues stayed basically the same and several new conclusions were drawn. Some cautions are presented concerning the state highway agency use of small sample sizes. Agencies are encouraged to perform their own optimization calculations. By doing so, agencies will gain a better understanding of their acceptance plan systems and associated costs and will have greater confidence in applying economic decision analysis principles to minimize expected costs and optimize statistical acceptance risks.
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