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Waverider has high lift to drag ratio and will be an idea aerodynamic configuration for hypersonic vehicles. But a structure permitting aerodynamic like waverider is still difficult to generate under airframe’s geometric constrains using traditional waverider design methods. And furthermore, traditional waverider’s aerodynamic compression ability cannot be easily adjusted to satisfy the inlet entrance requirements for hypersonic air-breathing vehicles. The purpose of this paper is to present a new method named osculating general curved cone (OCC) method aimed to improve the shortcomings of traditional waveriders.

A basic curved cone is, first, designed by the method of characteristics. Then the waverider’s inlet captured curve and front captured tube are defined in the waverider’s exit plane. Osculating planes are generated along the inlet captured curve and the designed curved cone is transformed to the osculating planes. Streamlines are traced in the transformed curved cone flow field. Combining all streamlines which have been obtained, OCC waverider’s compression surface is generated. Waverider’s upper surface uses the free stream surface.

It is found that OCC waverider has good volumetric characteristics and good flow compression abilities compared with the traditional osculating cone (OC) waverider. The volume of OCC waverider is 25 per cent larger than OC waverider at the same design condition. Furthermore, OCC waverider can compress incoming flow to required flow conditions with high total pressure recovery in the waverider’s exit plane. The flow uniformity in the waverider exit plane is quite well.

The analyzed results show that the OCC waverider can be a practical high performance airframe/forebody for hypersonic vehicles. Furthermore, this novel waverider design method can be used to design a structure permitting aerodynamic like waverider for a practical hypersonic vehicle.

The paper puts forward a novel waverider design method which can improve the waverider’s volumetric characteristics and compression abilities compared with the traditional waverider design methods. This novel design approach can extend the waverider’s applications for designing hypersonic vehicles.

Flood season in our country is characterized by frequent heavy rains, and flood problems are becoming increasingly serious. The uneven distribution of water resources causes conflicts in the occurrence of floods and droughts. Implementing effective flood control planning and solving drought and flood disasters are the research highlights of relevant institutions both domestic and abroad. This study develops a multiscale method of urban flood control planning based on microcirculation. A microcirculation water ecosystem, which consists of six elements, namely, collecting, interacting, precipitating, reserving, storing, and purifying, is introduced. This study investigates precipitation; peak shaving; recycle mode of filtration at the macro level in different regions; “hierarchy” in rainwater ecosystems in rain parks, heavy rain garden parks, and wetland parks at the meso level; and the concept of zero-emission rain in residential areas and roads at the micro level. Finally, this study analyzes a rain garden and its domestic application. A conclusion is drawn that the flood control planning model based on microcirculation can effectively reduce rain runoff. Empirical measurement proves that the proposed multiscale model for city flood control planning based on microcirculation promotes flood control and effectively reduces the occurrence of droughts and floods.

The purposes of this paper is twofold: first, to assess the risks associated with the international construction joint ventures (ICJVs) between Singapore and developing countries and second, to investigate the risk allocation preferences in these ICJVs.

A questionnaire survey was conducted and responses were received from 38 firms that had participated in ICJVs with developing countries. A risk criticality (RC) index was adopted to evaluate the criticality of each risk.

The survey results reported “political instability” as the most critical risk and market-level risks were less critical than country and project-level risks. Additionally, the results showed agreement on the risk ranking between building and infrastructure ICJVs, despite significant differences in the criticalities of five risks. Furthermore, five risks were preferably allocated to host and foreign partners, respectively, while 13 risks could be shared among partners.

First, due to the sample size, one should be cautious when interpreting and generalizing the results. Second, the RC index proposed in this study was subjective as it was influenced by the individual experience and risk attitude of the respondents. Also, the RC values were calculated without considering the weights of the respondents. Lastly, the questionnaire survey, which has been widely used in identifying risk allocation preferences, may not identify the insights of practitioners into the risk allocation practices.

This study provides a clear understanding of the risks associated with forming ICJVs with developing countries and the preferred risk allocation. Although, this study is focused on the risks faced by the Singapore-developing country ICJVs, the identification of the potential risks allows companies from other countries to customize their risk profile and assess the risks before they form ICJVs with developing countries.

As few studies have explored the risk allocation preferences in ICJVs, this study expands the literature and provides practitioners with important information for preparing joint venture contracts or agreements. Thus, this study can contribute to the literature relating to ICJVs.

The present study aims to develop a risk-supported case-based reasoning (RS-CBR) approach for water-related projects by incorporating various uncertainties and risks in the revision step.

The cases were extracted by studying 68 water-related projects. This research employs earned value management (EVM) factors to consider time and cost features and economic, natural, technical, and project risks to account for uncertainties and supervised learning models to estimate cost overrun. Time-series algorithms were also used to predict construction cost indexes (CCI) and model improvements in future forecasts. Outliers were deleted by the pre-processing process. Next, datasets were split into testing and training sets, and algorithms were implemented. The accuracy of different models was measured with the mean absolute percentage error (MAPE) and the normalized root mean square error (NRSME) criteria.

The findings show an improvement in the accuracy of predictions using datasets that consider uncertainties, and ensemble algorithms such as Random Forest and AdaBoost had higher accuracy. Also, among the single algorithms, the support vector regressor (SVR) with the sigmoid kernel outperformed the others.

This research is the first attempt to develop a case-based reasoning model based on various risks and uncertainties. The developed model has provided an approving overlap with machine learning models to predict cost overruns. The model has been implemented in collected water-related projects and results have been reported.