Asian Infrastructure Investment Bank’s president Mr. Jin Liqun shares with JIPD Editor-in-Chief, Dr. Gu Qingyang, his passion for infrastructure finance, as he reflects upon his goal of steering an environmentally friend and corruption-free AIIB toward building social-impacting infrastructure across Asia.
From governmental departments to international financial institutes, Mr. Jin Liqun has undertaken almost every essential role in finance. With his vast experience across the private and public sectors, particularly in multilateral development banks, Mr. Jin Liqun currently serves as Asian Infrastructure Investment Bank (AIIB)’s first President since its founding in 2016, following a stint as Secretary-General of the Multilateral Interim Secretariat created to establish the bank. Beginning from his two decades of governmental experience at the Chinese Ministry of Finance, rising from the rank of Deputy Director General to Vice Minister, Mr. Jin was then called to serve as Vice President, and then Ranking Vice President, of the Asian Development Bank, and later as Alternate Executive Director for China at the World Bank and at the Global Environment Facility. Mr. Jin had also served as Chairman of China International Capital Corporation Ltd., China’s first joint-venture investment bank, in addition to serving as Chairman of the Supervisory Board of the sovereign wealth fund China Investment Corporation and as Chairman of the International Forum of Sovereign Wealth Funds.

In this paper, an improved mathematical model for flashover behavior of polluted insulators is proposed based on experimental tests. In order to determine the flashover model of polluted insulators, the relationship between conductivity and salinity of solution pollution layer of the insulator is measured. Then, the leakage of current amplitude of four common insulators versus axial, thermal conductivity and arc constants temperature was determined. The experimental tests show that top leakage distance (TLd) to bottom leakage distance (BLd) ratio of insulators has a significant effect on critical voltage and current. Therefore, critical voltage and current were modeled by TLd to BLd ratio Index (M). Also, salinity of solution pollution layer of the insulators has been applied to this model by resistance pollution parameter. On the other hand, arc constants of each insulator in new model have been identified based on experimental results. Finally, a mathematical model is intended for critical voltage against salinity of solution pollution layer of different insulators. This model depends on insulator profile. There is a good agreement between the experimental tests of pollution insulators obtained in the laboratory and values calculated from the mathematical models developed in the present study.

Delay is the leading challenge in completing Engineering, Procurement, and Construction (EPC) projects. Delay can cause excess costs, which reduces company profits. The relationship between subcontractors and the main contractor is a critical factor that can support the success of an EPC project. The problematic financial condition of the main contractor can cause delay in payments to subcontractors. This research will set a model that combines the system dynamics and earned value method to describe the impact of subcontractor advance payments on project performance. The system dynamics method is used to model and analyze the impact of interactions between variables affecting project performance, while the earned value method is applied to quantitatively evaluate project performance and forecast schedule and cost outcomes. These two methods are used complementarily to achieve a holistic understanding of project dynamics and to optimize decision-making. The designed model selects the optimum scenario for project time and costs. The developed model comprises project performance, costs, cash flow, and performance forecasting sub-models. The novelty in this research is a new model for optimizing project implementation time and costs, adding payment rate variables to subcontractors and subcontractor performance rates. The designed model can provide additional information to assist project managers in making decisions.

To analyze the effect of an increase in the quantity or quality of public investment on growth, this paper extends the World Bank’s Long-Term Growth Model (LTGM), by separating the total capital stock into public and private portions, with the former adjusted for its quality. The paper presents the LTGM public capital extension and accompanying freely downloadable Excel-based tool. It also constructs a new infrastructure efficiency index, by combining quality indicators for power, roads, and water as a cardinal measure of the quality of public capital in each country. In the model, public investment generates a larger boost to growth if existing stocks of public capital are low, or if public capital is particularly important in the production function. Through the lens of the model and utilizing newly-collated cross-country data, the paper presents three stylized facts and some related policy implications. First, the measured public capital stock is roughly constant as a share of gross domestic product (GDP) across income groups, which implies that the returns to new public investment, and its effect on growth, are roughly constant across development levels. Second, developing countries are relatively short of private capital, which means that private investment provides the largest boost to growth in low-income countries. Third, low-income countries have the lowest quality of public capital and the lowest efficient public capital stock as a share of GDP. Although this does not affect the returns to public investment, it means that improving the efficiency of public investment has a sizable effect on growth in low-income countries. Quantitatively, a permanent 1 ppt GDP increase in public investment boosts growth by around 0.1–0.2 ppts over the following few years (depending on the parameters), with the effect declining over time.

The Organic Rankine Cycle (ORC) is an electricity generation system that uses organic fluid instead of water in the low temperature range. The Organic Rankine cycle using zeotropic working fluids has wide application potential. In this study, data mining (DM) model is used for performance analysis of organic Rankine cycle (ORC) using zeotropik working fluids R417A and R422D. Various DM models, including Linear Regression (LR), Multi-Layer Perceptron (MLP), M5 Rules, M5 Model Tree, Random Committee (RC), and Decision Tree (DT) models are used. The MLP model emerged as the most effective approach for predicting the thermal efficiency of both R417A and R422D. The MLP’s predicted results closely matched the actual results obtained from the thermodynamic model using Genetron software. The Root Mean Square Error (RMSE) for the thermal efficiency was exceptionally low, at 0.0002 for R417A and 0.0003 for R422D. Additionally, the R-squared (R²) values for thermal efficiency were very high, reaching 0.9999 for R417A and R422D. The findings demonstrate the effectiveness of the DM model for complex tasks like estimating ORC thermal efficiency. This approach empowers engineers with the ability to predict thermal efficiency in organic Rankine systems with high accuracy, speed, and ease.

In order to study the temperature change trend of the surrounding geotechnical soil during the operation and thermal recovery of the medium-deep geothermal buried pipe and the influence of the geotechnical soil on the operational stability of the vertical buried pipe after thermal recovery. Based on the data of geological stratum in Guanzhong area and the actual engineering application of medium-deep geothermal buried pipe heating system in Xi’an New Area, the influence law of medium-deep geothermal buried pipe heat exchanger on surrounding geotechnical soil is simulated and analyzed by FLUENT software. The results show that: after four months of heating operation, in the upper layer of the geotechnical soil, the reverse heat exchange zone appears due to the higher fluid temperature; in the lower layer of the geotechnical soil, the temperature decreases more with the increase of depth and shows a linear increase in the depth direction; without considering the groundwater seepage, after eight months of thermal recovery of the geotechnical soil after heating, the maximum temperature difference after recovery is 3.02 ℃, and the average temperature difference after recovery is 1.30 ℃ The maximum temperature difference after recovery was 3.02 ℃ and the average temperature difference after recovery was 1.30 ℃. The geotechnical thermal recovery temperature difference has no significant effect on the long-term operation of the buried pipe, and it can be operated continuously and stably for a long time. Practice shows that due to the influence of various factors such as stratigraphic structure, stratigraphic pressure, radioactive decay and stratigraphic thermal conductivity, the actual stratigraphic temperature below 2000m recovers rapidly without significant temperature decay, fully reflecting the characteristics of the Earth’s constant temperature body.