Risk assessment is one of the most important factors in achieving success in public-private partnership (PPP) projects. Some relationships between risks in freeway projects have been established. The occurrence of each risk can worsen the effects of others such as a negative impact of financial risks on construction risks. This paper is aimed at prioritizing significant risks in freeway PPP projects applying a fuzzy analytic network process (FANP) method for overcoming the problems of interdependencies and feedback among different risk-ranking alternatives. Data on the study have been collected through a literature review, an interview and a questionnaire survey distributed to experts in the field of freeway PPP projects. The obtained results have shown that financial, legal and political risks are the most significant groups, although improper design, changes in the value of granted lands and the termination of concession are the most important risks. The findings help with strengthening the capabilities of developing countries for risk management in freeway PPP projects.

The Newberry Volcano EGS Demonstration is a 5 year field project designed to demonstrate recent technological advances for engineered geothermal systems (EGS) development. Advances in reservoir stimulation, diverter, and monitoring are being tested in a hot (>300°C), dry well (NWG 55-29) drilled in 2008. These technologies could significantly reduce the cost of electrical power generation from geothermal resources. The project, funded in part by the Department of Energy, began in 2010 with two years of permitting, technical planning, and development of a project-specific Induced Seismicity Mitigation Plan (ISMP). Well stimulation carried out in 2012 indicated that casing repairs were needed; confirmed by further wellbore logging and analysis in 2013. Repairs were completed in August 2014, and the well was re-stimulated in the fall. 9,500 m 3 (2.5 million gallons) of groundwater were injected at a maximum wellhead pressure of 195 bar (2850 psi) over 4 weeks of hydraulic stimulation. Injectivity changes, thermal profiles and seismicity indicate that fracture permeability in well NWG 55-29 was enhanced. The fifteen-station microseismic array (MSA) located 398 events in 2014, ranging in magnitude from M 0 to M 2.26. Temperature logs run after injection of thermally-degradable zonal isolation material (TZIM) showed that at least two flow zones were blocked and one or two new zones opened because of the injected TZIM. Breakdown products of TZIM were detected in flow-back fluids, indicating that the material degraded as predicted. This work demonstrates the viability of large-volume low-pressure stimulation coupled with non-mechanical diverter technology and microseismic monitoring for reservoir mapping.

Existing risks in deep foundation excavation projects is a major issue in developing cities. With the rapid increase in the number of various deep foundation and excavation projects in big cities of Iran, many accidents related to deep excavation have been reported every year. These accidents affected delay and increased cost of project implementation. Therefore identification and assessment of risks of these accidents is essential. The aim of the research was to develop a framework to overcome limitations of previous approaches to assess of risks in excavation projects. According to the complexity of a problem and the inherent uncertainty, the framework adopted SWARA (Step-wise Weight Assessment Ratio Analysis) and COPRAS (COmplex PRoportional ASsessment) methods through introducing new criteria for risk assessment. Data was collected through interview, a literature review and a questionnaire survey distributed to excavation project experts. A case study of deep foundation excavation in Shiraz was presented. The results have shown that the risks involving construction safety, unfavourable geological conditions, shortage of managerial experience, incomplete emergency plan and subsidence of ground are the most significant risks excavation projects in Shiraz. The proposed framework and the obtained results can help stakeholders of excavation projects in developing countries better to manage project risks. Research interests: many miscellaneous management areas (enterprise, construction project and etc.), risk assessment, construction project administration, building life-cycle, construction technology and organisation, decision-making and grey system theory, Decision Making (DM), statistics, optimization, strategies, game theory, intelligent support system, Sustainable Development: developing of alternative construction processes, economic and other aspects, sustainable development challenges for business and management in construction enterprises, environmental impact processes and etc.

The decision making for risk allocation problems in public–private partnership (PPP) projects is a vital process that directly affects the timeliness, cost, and quality of the project. Fair risk allocation is a vital factor to achieve success in the implementation of these projects. It is essential for private and public sectors to apply efficient risk allocation approaches to experience a more effective process of agreement arbitration and to reduce the appearance of dispute during the concession period. The aim of this study is to develop an optimization approach to enhance risk allocation process in PPP projects. The shared risks in projects are identified through comprehensive literature review and questionnaire survey obtained from Malaysian professionals involved in PPP projects. Objective functions are then developed to minimize the total time and cost of the project and maximize the quality while satisfying risk threshold constraints. The combinatorial nature of the risk allocation problem describes a multi-objective situation that can be simulated as a knapsack problem (KP). The formulation of the KP is described and solved applying genetic algorithm (GA). Due to the flexibility of GA, the results are Pareto Optimal solutions that describe the combinations of risk percentages for shared risks in PPP projects.

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