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The purpose of this paper is to demonstrate the effect of δ-ferrite on the susceptibility to hydrogen embrittlement of type 304 stainless steel in hydrogen gas environment.

The mechanical properties of as-received and solution-treated specimens were investigated by the test of tensile and fatigue crack growth (FCG) in 5 MPa argon and hydrogen.

The presence of δ-ferrite reduced the relative elongation and the relative reduction area (H₂/Ar) of 304 stainless steel, indicating that δ-ferrite increased the susceptibility of hydrogen embrittlement in 304 stainless steel. Moreover, δ-ferrite promoted the fatigue crack initiation and propagation at the interface between δ-ferrite and austenite. The FCG tests were used to investigate the effect of δ-ferrite on the FCG rate in hydrogen gas environment, and it was found that δ-ferrite accelerated the FCG rate, which was attributed to rapid diffusion and accumulation of hydrogen around the fatigue crack tip through δ-ferrite in high-pressure hydrogen gas environment.

The dependence of the susceptibility to hydrogen embrittlement on δ-ferrite was first investigated in type 304 steel in hydrogen environment with high pressures, which provided the basis for the design and development of a high strength, hydrogen embrittle-resistant austenitic stainless steel.

This paper aims to explore the influence of CO₂ partial pressure, flow rate and water cut on N80 steel corrosion behaviors in the displacement process of oil in glutenite reservoir by CO₂ injection.

A self-made 3 L high-temperature and high-pressure autoclave was used to conduct corrosion simulation experiments of N80 steel in different CO₂ partial pressures, flow rates and water cut (the independently developed oil and water mixing approach can ensure the uniform mixing of oil and water in experiments). Techniques like weight loss and surface analysis were used to analyze the corrosion behaviors of N80 steel under different conditions.

Results showed that the average corrosion rate of N80 steel accelerated at varying degrees with the increase of CO₂ partial pressure, flow rate and water cut. Excluding that the samples showed uniform corrosion under the two conditions of 0.5MPa CO₂ partial pressure and static corrosion, they displayed mesa attack corrosion under other conditions. Besides, with the increase of CO₂ partial pressure, the pH value of solution dropped and the matrix corrosion speed rose, hence leading to the increased Fe²⁺ and CO₃²⁻ concentration. Meanwhile, a lowered pH value improved the FeCO₃ critical supersaturation, thereby leading to an increased nucleation rate/growth rate and ultimately causing the decrease of the dimension of FeCO₃ crystallites formed on the surface of the samples.

The results can be helpful in targeted anti-corrosion measures for CO₂/oil/water corrosive environment.

This paper aims to investigate the high-temperature mechanical properties of HS110S steel and its corrosion behaviors in harsh downhole environment.

In this work, mechanical property measurements were carried out from 25°C to 350°C and the scanning electron microscopy was used to observe the fracture morphology. The weight-loss measurements and surface characterization were used to evaluate the corrosion resistance of HS110S steel in harsh downhole environment.

Results show that the yield strength and tensile strength of HS110S steel at 350 °C are 779 and 861 MPa, respectively. Compared with room temperature, the reduction rate values are both less than 20%. At the high-temperature corrosion environment (350 °C), the static and dynamic corrosion rates are 0.9668 and 1.9236 mm/a, respectively. The generated corrosion products are mainly composed of FeSx, FeCO₃ and Fe₃O₄. Therefore, the HS110S steel applied under such conditions needs to take suitable protective measures.

In general, the HS110 steel has widely used in conventional development conditions (e.g. low H₂S or high CO₂ environments). However, to the best of the authors’ knowledge, no studies have reported on its application at more than 250°C. Therefore, this work can be a reference to the application of HS110S steel in high-temperature corrosion conditions.

The purpose of this paper is to propose a new hybrid algorithm, named improved plant growth simulation algorithm and particle swarm optimization hybrid algorithm (PGSA–PSO hybrid algorithm), for solving structural optimization problems.

To further enhance the optimization efficiency and precision of this algorithm, the optimization solution process of PGSA–PSO comprises two steps. First, an excellent initial growth point is selected by PSO. Then, the global optimal solution can be obtained quickly by PGSA and its improved strategy called growth space adjustment strategy. A typical mathematical example is provided to verify the capacity of the new hybrid algorithm to effectively improve the global search capability and search efficiency of PGSA. Moreover, PGSA–PSO is applied to the optimization design of a suspended dome structure.

Through typical mathematical example, the improved strategy can improve the optimization efficiency of PGSA considerably, and an initial growth point that falls near the global optimal solution can be obtained. Through the optimization of the pre-stress of a suspended dome structure, compared with other methods, the hybrid algorithm is effective and feasible in structural optimization.

Through the examples of suspended dome structure, it shows that the optimization efficiency and precision of PGSA–PSO are better than those of other algorithms and methods. PGSA–PSO is effective and feasible in structural optimization problems such as pre-stress optimization, size optimization, shape optimization and even topology optimization.

The purpose of this paper is to propose a new hybrid algorithm, named improved plant growth simulation algorithm and genetic hybrid algorithm (PGSA-GA), for solving structural optimization problems.

PGSA-GA is based on PGSA and three improved strategies, namely, elitist strategy of morphactin concentration calculation, strategy of intelligent variable step size and strategy of initial growth point selection based on GA. After a detailed formulation and explanation of its implementation, PGSA-GA is verified using the examples of typical truss and single-layer lattice shell.

Improved PGSA-GA was implemented and optimization was carried out for two typical optimization problems; then, a comparison was made between the PGSA-GA and other methods. The results show that the method proposed in the paper has the advantages of high efficiency and rapid convergence, which enable it to be used for the optimization of various types of steel structures.

Through the examples of typical truss and single-layer lattice shell, it shows that the optimization efficiency and effect of PGSA-GA are better than those of other algorithms and methods, such as GA, secondary optimization method, etc. The results show that PGSA-GA is quite suitable for structural optimization.

This paper aims to establish a model to evaluate the benefits of building information modeling (BIM) from the owners' perspective. The model analyzes the correlation between five secondary benefit indicators and their subsystems: product, financial, organizational, management and strategic. The final key factors of BIM benefits provide a decision-making basis for owners to raise the efficiency of BIM application.

Firstly, the authors combed 31 BIM-related literature and interviewed experts to identify 15 preliminary benefit indicators. The authors established a BIM benefit evaluation system based on relevant concepts, including two primary indicators, five secondary indicators and 15 tertiary indicators. Secondly, the authors analyzed the indicators by the extension theory of matter element analysis and a questionnaire survey of expert opinion. Finally, the new method was applied to a case study of a large shopping center in east China for empirical verification.

A BIM benefit evaluation model, including a three-tiered hierarchy of primary, secondary and tertiary indicators, was constructed through literature review and expert opinions. The model determined the critical factors of BIM benefits, enhanced understanding of owner benefits and improved BIM application under the owners' leadership.

At present, most studies focus on specific project stages or benefit indicators. This study developed an integrated BIM benefit evaluation system that targets owners. The findings could foster the development of China's construction industry, promote owner-led BIM application and advocate adopting the benefit evaluation method.

The purpose of this research is to prepare a dispersion resin with good dispersity and a colour paste with good stability. At present, the colour paste is being prepared using the pigment dispersion resin which has the group quaternary ammonium. The dispersion resin prepared has good dispersity of pigment and extender. However, the stability of storage and construction of the colour paste is relatively poor, which has a negative influence on the application of cathodic electrodeposited (CED) coatings. However, the detailed investigation on the dispersion resin and the stable colour paste has not been reported.

Three steps are adopted to prepare the dispersion resin, that is blocking toluene diisocyanate (TDI), quaternary ammoniation of blocked TDI and ring opening of epoxy resin. The resultant dispersion is used to prepare the colour paste. The factors, which have an influence on the dispersity of the dispersion resin and stability of the colour paste, are optimised.

The typical recipes of preparing the dispersion resin and the resultant colour paste are obtained. The dispersity of the dispersion resin and stability of the colour paste are good based on the typical recipe. In addition, the film of the CED coating is smooth, dense and hard when the colour paste is used in the CED coating.

The dispersion resin can be used to prepare a colour paste, which can be used in the CED coatings. In addition, it also can be applied as a binder of coatings and adhesions.

The factors, which have an influence on the dispersity of the dispersion resin and stability of the colour paste, are studied in detail. The typical recipes of preparing the dispersion resin and the resultant colour paste are obtained. Based on the typical recipe, the dispersity of the dispersion resin and stability of the colour paste are good.

The purpose of this paper is to examine the different strategies implemented by a number of successful Chinese firms currently striving to build global brands in order to improve their export capabilities. A particular emphasis is put on the transfer of marketing technology for brand engineering in order to achieve this goal.

The analysis uses case study methodology to understand what many prominent Chinese exporting firms have achieved, and develops a theory about their general strategy. Five firms have been chosen: Lenovo, Haier, Cosco, Tsingtao, Geely. Aside from these five, information is also given on the branding strategy of Li Ning and Suntech Power. A great part of the information collected is coming from “desk research”, except for Haier, Lenovo and Tsingtao for which personal contacts and visits took place in 2005 and 2006.

The findings suggest that some of the most successful Chinese firms in the field of development of brand image either use some marketing tools, such as increasing their communication spending, improving quality control, emphasizing their corporate social responsibility visibility, or by seeking a partnership through mergers/acquisition with successful foreign brands. A basic global branding model has been defined as consistent with Chinese firms’ experience.

The study was limited to seven firms to be considered among the most successful Chinese businesses. It does not intend to be perceived as statistically representative. The period of observation of the effect of the strategy which was implemented was short and during a time of booming Chinese economy. It was impossible to isolate the extraneous variables linked to the economic or competitive situation, knowing that they could affect the observations on the firms that were studied.

Though the entry strategies on the Chinese market as well as inbound foreign direct investments have been the object of a great number of publications, the outbound strategies of Chinese exporting firms, as well as the impact of technology transfer, has been covered less frequently. Therefore, this paper can have value for candidates for the improvement of global branding.

Recent research on the energy system highlights the need for understanding the bandwidth of drivers and inhibitors of household investor's behaviour in rooftop PV (or photovoltaic power system) and to fit the broader socio-economic context in which they are deployed. However, apart from few exceptions, these newer perspectives have not been duly applied in the research on rooftop PV. This paper aims to fill this gap and to shed new light on rooftop PV investment decisions.

This study has been conducted with the primary data collected using two data sets of 237 households and 387 households of Indian southern state Kerala using survey-based questionnaire. The findings from first data set revealed that households considering the adoption of PV were likely influenced by six distinct factors, three motivators and three inhibitors. Second data set for multi-state analytic approach was proposed whereby the research model was tested using structural equation modelling (SEM). The outcomes of SEM were used as inputs for an artificial neural network (ANN) model for forecasting investor investment decision in in renewables. The ANN model was also used to rank the relative influence of significant predictors obtained from SEM.

In line with the risk–return framework, government subsidies act as primary motivator which helps in overcoming the initial risk of investment in the new technology. Further, low prices and low cost of maintenance are some of the financial motivators which may likely mitigate the long-term apprehension of returns and maintenance cost. Lastly, the strongest motivators of PV investment come from the environmental and financial motivator in the form of PV subsidies, which further solidifies the role of policy interventions in investment decision. The ANN model identified the technical barrier and knowledge and awareness factors play a significant role in forcasting the investor investing decision.

The study results will be useful for policymakers for framing strategies to attract and influence their investment in renewable energy.

Building upon behavioural finance and institutional theory, this paper posits that, in addition to a rational evaluation of the economics of the investment opportunities, various non-financial factors affect the household's decision to invest in renewables.