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To ensure the reliable and safe operation of elevated-temperature pipes and equipment in the long term, it is essential to thoroughly assess the creep rupture life. Nevertheless, there is currently no design code that specifies a creep rupture life evaluation method for non-nuclear elevated-temperature equipment. The paper aims to discuss this issue.

An analysis was conducted to compare the differences and conservativeness in calculating creep strain using three major codes (ASME-CC-2843, API-579 and BS-7910) based on the results of the 316H creep constitutive model and creep strain prediction. In addition, the creep resistances of 316H, 304H and 347H were compared. Subsequently, the ANSYS Usercreep subroutine was developed to compare the discrepancies between different codes under multiaxial stress conditions using numerical simulations.

BS-7910 employs the Norton creep model with calculation parameters for the average creep strain rate, which is not applicable for the engineering design stage. ASME-CC2843 code primarily focuses on the primary and secondary creep stages, making it more suitable for non-nuclear pipeline and equipment design. For 316H, the creep strain curves predicted by ASME-CC2843 and API-579 typically intersect at a specific point. By combining the creep strain predicted by ASME-CC2843 and API-579, 347H exhibits superior predicted creep resistance compared to 316H, whereas 316H exhibited better predicted creep resistance than 304H.

This study provides a guide for future evaluation methods and material choices for non-nuclear equipment and pipelines operating at elevated temperatures.

To ensure the stable operation of ironmaking process and the quality and output of sinter, the multi-objective optimization of sintering machine batching process was carried out.

The purpose of this study is to establish a multi-objective optimization model with iron taste content and batch cost as targets, constrained by field process requirements and sinter quality standards, and to propose an improved balance optimizer algorithm (LILCEO) based on a lens imaging anti-learning mechanism and a population redundancy error correction mechanism. In this method, the lens imaging inverse learning strategy is introduced to initialize the population, improve the population diversity in the early iteration period, avoid falling into local optimal in the late iteration period and improve the population redundancy error correction mechanism to accelerate the convergence rate in the early iteration period.

By selecting nine standard test functions of BT series for simulation experiments, and comparing with NSGA-?, MOEAD, EO, LMOCSO, NMPSO and other mainstream optimization algorithms, the experimental results verify the superior performance of the improved algorithm. The results show that the algorithm can effectively reduce the cost of sintering ingredients while ensuring the iron taste of sinter, which is of great significance for the comprehensive utilization and quality assurance of sinter iron ore resources.

An optimization model with dual objectives of TFe content and raw material cost was developed taking into account the chemical composition and quality indicators required by the blast furnace as well as factors such as raw material inventory and cost constraints. This model was used to adjust and optimize the sintering raw material ratio. Addressing the limitations of existing optimization algorithms for sintering raw materials including low convergence accuracy slow speed limited initial solution production and difficulty in practical application we proposed the LILCEO algorithm. Comparative tests with NSGA-III MOEAD EO LMOCSO and NMPSO algorithms demonstrated the superiority of the proposed algorithm. Practical applications showed that the proposed method effectively overcomes many limitations of the current manual raw material ratio model providing scientific and stable decision-making guidance for sintering production operations.

This paper explores the association between directors’ and officers’ liability insurance (D&O insurance) and management tone manipulation.

This study uses data from A-share listed non-financial companies from 2009 to 2021 as its sample for empirical tests. In addition, the study relies on text analysis and the construction of models to investigate the relationship between D&O insurance and management tone manipulation.

The authors find that the purchase of D&O insurance will lead to management tone manipulation in the “management discussion and analysis” part of companies’ annual reports, and operating risk and agent cost are the two paths for the effect. Further analysis shows that having a male CEO and employing high-quality auditors can weaken the positive impact of D&O insurance on tone manipulation.

This paper provides a new approach for studying the literature related to D&O insurance and management behavior, and the findings enrich our understanding of the influencing factors and the mechanism of management tone manipulation, thus revealing policy implications for further standardization of the terms and system of D&O insurance in China.

This study aims to analyze government hotline text data and generating forecasts could enable the effective detection of public demands and help government departments explore, mitigate and resolve social problems.

In this study, social problems were determined and analyzed by using the time attributes of government hotline data. Social public events with periodicity were quantitatively analyzed via the Prophet model. The Prophet model is decided after running a comparison study with other widely applied time series models. The validation of modeling and forecast was conducted for social events such as travel and educational services, human resources and public health.

The results show that the Prophet algorithm could generate relatively the best performance. Besides, the four types of social events showed obvious trends with periodicities and holidays and have strong interpretable results.

The research could help government departments pay attention to time dependency and periodicity features of the hotline data and be aware of early warnings of social events following periodicity and holidays, enabling them to rationally allocate resources to handle upcoming social events and problems and better promoting the role of the big data structure of government hotline data sets in urban governance innovations.

Environmental pollution has been a great concern for the government of Bangladesh. Bangladesh was the least developed country, with a lot of financial challenges. The industrial process in Bangladesh has not been able to maintain the directives of the SDGs. The lack of proper industrial policy, technological backwardness and lacunae in implementing environmental governance have affected the environment of the country. The unorganised and informal manufacturing units are often accused of emitting greenhouse gases. Like other South Asian countries, the informal manufacturing sector in Bangladesh has been established without proper planning and environmental guidelines. In Bangladesh, the informal sector includes brick kilns, food processing factories, leather tanning, etc., which are responsible for environmental pollution, health hazards and violations of SDG goals. The issue of environmental pollution by the informal manufacturing sectors of Bangladesh needs to be investigated in the context of the socioeconomic profile of the country and the performance of the government in monitoring the issue. Due to the lack of environmental governance, a high level of pollution has been occurring in the country. What kinds of economic tools and industrial policies are needed to be implemented to avoid environmental hazards? The content analysis method will be applied in this chapter.

This study aims to address the degradation and damage of traditional bridge expansion joints by proposing a seamless expansion joint device based on polyurethane elastomer (PUE).

A series of laboratory experiments were conducted to evaluate the performance of PUE, including elasticity recovery, interfacial bonding and hygrothermal aging tests. Indoor model tests were also designed to analyze PUE's performance in actual bridge expansion structures. Based on these evaluations, the design of a seamless PUE expansion joint structure was completed.

The study reveals that PUE achieves optimal interfacial bond strength with PUC at −30°C after 7 h of curing and adhesive application, with a tensile strength of 9.2 MPa. PUE's elongation at break exceeds 3% at −30°C and retains its toughness and tensile strength after hygrothermal aging. When the beam end rotation reaches 0.0144 rad, PUE maintains a linear elastic state. With a groove width of 340 mm, PUE can withstand compressive displacements over 40 mm and tensile displacements up to 60 mm.

The findings highlight the excellent elasticity recovery and toughness characteristics of PUE, demonstrating the significant improvement in durability of the PUE seamless expansion joint structure and the rationality of the groove width calculation method based on the elongation at break of PUE. The broader impact of this study lies in its potential to innovate the design and maintenance strategies of bridge expansion joints.

The interplay between individual and collective creativity and its translation into innovation is a critical yet complex challenge in the ever-evolving innovation landscape. This study delves into the intricate relationship between managerial ability, intellectual property rights (IPRs) and research and development (R&D) investments contextualized within the dynamics of leverage, firm life stages and tangibility for pharmaceutical firms in the Asia-Pacific region. By exploring how micro-level factors influence macro-level innovation processes, this study aims to contribute to the broader understanding of creativity and innovation, a theme at the heart of addressing contemporary global challenges.

Econometric methodologies were used to analyse a data set comprising 2,660 firm-year observations spanning the decade from 2011 to 2020.

A key finding was that companies with lower managerial prowess strategically leverage R&D intensity to signal their value to the market and accrue reputational currency. The research unearths a significant positive relationship between managerial ability, IPRs and R&D investment. In environments characterized by strong managerial acumen and robust IPR safeguards, firms exhibit a heightened propensity to allocate resources to R&D endeavours. This underscores the role of intellectual leadership and legal protections in shaping R&D strategies within the pharmaceutical domain. Incorporating firm life stages as a moderating factor reveals that firm maturity fundamentally influences the interplay between managerial ability, IPRs and R&D expenditure.

These findings’ implications resonate profoundly within policy-making circles and pharmaceutical firms’ day-to-day operational strategies, underscoring the pivotal role of intellectual capital and legal safeguards in shaping the future of innovation in the Asia-Pacific pharmaceutical sector.

Drawing from the social exchange theory and leadership-making model, this study aimed to develop a research model where innovation climate (IC) mediates the servant leadership (SL) influence on innovative work behavior (IWB).

Through structural equation modeling, we evaluated the aforementioned links using data gathered from 324 employees drawn from Uganda’s local government (LG) employees.

The findings show that the impact of SL on IWB is mediated by IC. An IC within the organization is made possible by effective SL ethos; moreover, this climate promotes IWB. Also, the innovative nature of LG employees promotes IWB.

LG leadership ought to be committed to the SL philosophy since it fosters an environment that encourages IWB. To spark IWB, it should also take advantage of the innovative environment. Management must make sure that in such a setting, supervisors are construed as servant leaders and low cadre staff have the capacity to be servant leaders. Employees will be more motivated to contribute to the organization by engaging in high IWB once they have received the training, empowerment and rewards they deserve in a setting that emphasizes effective SL principles.

Despite the existence of numerous studies, there is little empirical evidence that SL influences IWB within the setting of the LG sector. Evidence for the underlying mechanism by which SL promotes IWB is still lacking. Third, we explicitly test the IWB model developed based on euro-leaning theories using the LG context. Finally, there is a dearth of data relevant to how IC affects IWB. The research addresses these gaps.

The effect of spinning has been studied and analysed for different projectile shapes such as ogive, blunt, cylindrical and conical by using numerical simulations.

Projectile shape is one of the important parameters in the penetration mechanism. The present study deals with the failure mechanisms and ballistic evaluation for different nose-shaped projectiles undergoing normal impact with spinning. Materials characterization has been made by Johnson–Cook strength and failure models, and LS-DYNA simulations are used to analyse the impact of steel projectiles on an Al 7075-T651 target at different impact velocities under normal impact conditions. The experimental results from the literature are used to validate the model. Based on the residual velocity values, the Recht-Ipson model has been curve-fitted and approximate ballistic limit velocity has been evaluated. The approximated ballistic limit velocity is found to be 3.4% higher than the experimental results and compared well with the experimental results. Subsequently, the validated model conditions are used to study and analyse the effect of spinning for different nose-shaped projectiles undergoing normal impact conditions.

The ductile hole failure is observed for the ogive nose projectile, petals are formed and fragmented for the conical projectile, and plugging is observed for cylindrical projectiles. A Recht-Ipson curve is presented for each spinning condition for each projectile shape and the ballistic limit has been evaluated for each condition.

The proposed research outputs are original and innovative and, have a lot of importance in defence applications, particularly in arms and ammunition.

This study aims to investigate the impact of brain drain on government AI readiness in EU member countries, considering the distinctive governance characteristics, macroeconomic conditions and varying levels of ICT specialists.

The research employs a dynamic panel data model using the System Generalized Method of Moments (GMM) to analyze the relationship between brain drain and government AI readiness from 2018 to 2022. The study incorporates various control variables such as GDP per capita growth, government expenditure growth, employed ICT specialists and several governance indicators.

The results indicate that brain drain negatively affects government AI readiness. Additionally, the presence of ICT specialists, robust governance structures and positive macroeconomic indicators such as GDP per capita growth and government expenditure growth positively influence AI readiness.

Major limitations include the focus on a specific region of countries and the relatively short period analyzed. Future research could extend the analysis with more comprehensive datasets and consider additional variables that might influence AI readiness, such as the integration of AI with emerging quantum computing technologies and the impact of governance reforms and international collaborations on AI readiness.

The theoretical value of this study lies in providing a nuanced understanding of how brain drain impacts government AI readiness, emphasizing the critical roles of skilled human capital, effective governance and macroeconomic factors in enhancing AI capabilities, thereby filling a significant gap in the existing literature.

This research fills a significant gap in the existing literature by providing a comprehensive analysis of the interaction between brain drain and government AI readiness. It uses control variables such as ICT specialists, governance structures and macroeconomic factors within the context of the European Union. It offers novel insights for policymakers to enhance AI readiness through targeted interventions addressing brain drain and fostering a supportive environment for AI innovation.