Fluor Corporation is an American multinational engineering and construction firm headquartered in Irving, Texas. It is a holding company that provides services through its subsidiaries in the following areas: oil and gas, industrial and infrastructure, government and power. It is the largest publicly traded engineering & construction company in the Fortune 500 rankings and is listed as 259th overall.Fluor was founded in 1912 by John Simon Fluor as Fluor Construction Company. It grew quickly, predominantly by building oil refineries, pipelines, and other facilities for the oil and gas industry, at first in California, and then in the Middle East and globally. In the late 1960s, it began diversifying into oil drilling, coal mining and other raw materials like lead. A global recession in the oil and gas industry and losses from its mining operation led to restructuring and layoffs in the 1980s. Fluor sold its oil operations and diversified its construction work into a broader range of services and industries.In the 1990s, Fluor introduced new services like equipment rentals and staffing. Nuclear waste cleanup projects and other environmental work became a significant portion of Fluor's revenues. The company also did projects related to the Manhattan Project, rebuilding after the Iraq War, recovering from Hurricane Katrina and building the Trans-Alaska Pipeline System.
This study investigated the shear behavior of reinforced concrete (RC) beams strengthened with externally bonded (EB) fiber-reinforced polymer (FRP) strips, focusing on the size effect and the shear contribution of both concrete and FRP strips. Small-, mid-, and large-scale RC beams were tested to evaluate the shear strength gain and the effective strain of FRP strips. The results show that the shear strength gain decreases as beam size increases, indicating a size effect. Additionally, the shear strength gain is not equal to the shear contribution of the FRP strips, suggesting that an interaction between concrete and FRP strips exists. The effective strain of the FRP strips decreased with increasing beam size, corresponding to 37
In order to support scientific reviewing in the area of material property research and make the reviewing process easier and more efficient, checklists covering typical problems, lists of available resources, and computer-based and online tools to help compose reviewers' reports have been created. Our intention is to ensure that scientific communications show necessary and sufficient primary and supporting information about substances studied, conditions, properties, and techniques of interest with understandable terminology, in detail assuring reproducibility of the obtained results. The principles and ideas of this project can be extended to other scientific areas.
Purpose Generative artificial intelligence (GenAI) holds significant potential to improve accuracy, reduce uncertainties and support proactive financial decision-making throughout the project lifecycle. Despite these promising capabilities, the adoption of generative AI in construction cost management remains limited and uneven. This study, therefore, aims to examine the barriers to adopting GenAI for cost management in the Nigerian construction industry and to propose viable strategies to overcome them. Design/methodology/approach A quantitative research approach was adopted, with data collected through structured, closed-ended questionnaires administered to construction professionals. The data were analysed using both descriptive and inferential statistical techniques. Findings The study identified nine critical barriers to the adoption of GenAI for cost management in the Nigerian construction industry. Exploratory factor analysis grouped these barriers into two principal components: internal organisational constraints and external risk and environmental uncertainty factors. The results highlight that GenAI adoption is a socio-technical process influenced by both organisational readiness and external conditions. In addition, the study provides practical value by developing a structured matrix that aligns each barrier with targeted strategies across technology, people, process and risk management dimensions, offering actionable guidance for improving adoption. Originality/value This study contributes to digital transformation in construction by providing empirical, context-specific evidence on the adoption of GenAI for cost management in the Nigerian construction industry. It identifies and categorises nine critical barriers into internal organisational constraints and external risk and environmental uncertainty factors. The study further develops a structured matrix that links these barriers to targeted strategies across the technology, people, process and risk management dimensions. In addition, it extends the technology acceptance model by demonstrating how organisational and environmental factors influence GenAI adoption in a complex context.
When an operating air condenser fell short of meeting its design heat duty on hot summer days, a troubleshooting team set out to determine the cause.
There is currently confusion and differing practices being specified by purchasers, Shell-and-Tube Heat Exchanger (S&T HX) fabricators and/or U-bend suppliers regarding when and how to heat treat tubing U-bends. The need for Heat Treatment (HT) varies based on the material, service, and tightness of the bend (i.e., the degree of strain). The methods used for heat treating are typically furnace or Electric-Resistance (ER). This paper first summarizes the international codes and standards requirements for S&T HX U-bend heat treatment. Next it provides the highlight of some industry studies and compiles case histories of U-bend failures from literature and conference minutes. The overall goal for this paper is to propose possible initial changes to the relevant standards with future changes being added after the additional testing.
