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Cost and schedule overruns are rife in dam projects. Normative evidence espouses overruns as though they are inimical to development and prosperity aspirations of stakeholders. This study examines the causal relationship between project financing and overruns.

Causative data were extracted from completion reports of 28 major dam projects in Africa. Each of the projects was financed jointly by up to 10 international development lenders. Relationships between causes of overruns and project outcomes were analysed.

Analyses elicit indicators of remarkable correlations between finance procedures and project outcomes. Lenders’ disposition to risk attenuation was the main debacles to project success. Interests had mounted, whilst release of fund was erratic and ill-timed. Finance objectives and mechanisms were grossly inadequate for projects’ intense bifurcations. Projects had slowed or stalled because lenders’ risks attenuation processes were purposed to favour lenders’ objectives, and not projects’ interests. In addition, findings also show project owners’ own funds and the number of lenders to a single project correlate with overruns.

Findings imply commercial complexities around major projects. They also show transactions are shaped by subtle (mis)trust behaviours in project finance procedures. Thus, scholarly solutions to project performance issues should consider behavioural issues of stakeholding parties more broadly, beyond contractors and project owners. Project finance ecosystems are vulnerable to major actors’ self-interests, opportunism and predatory conducts. Borrowers would manage this by developing and improving their capacity to build resilience and trust. Evidence shows intense borrower nations in Africa have limited capacity and acuity for these.

This study contextualises megaprojects in complexity rather than cost. Its additionality is in how finance steers absolute control of project environment away from project owners and how finance administration triggers risks and overrun.

The study is called for to eliminate the noise between the significant macro variables from the perspective of the cause-and-effect approach to indicate why and how the return of solar projects is being affected by these.

The study aims to investigate the spread between unit selling electricity prices of a monthly production of 250 KW solar project installed in Türkiye and USD/TRY.

A relational framework is designed by drawing on the variables determined as crude oil prices, United States (US) 2-year yield, Dollar Index (DXY), USD/TRY, the annual inflation rate of Türkiye, and unit selling electricity prices. Then, a multivariate approach is performed through Matlab to analyse the correlational relationships and structure the curve estimation models.

The observations show that the gradually rising spread between unit selling electricity price and USD/TRY signals the reduction in return-on-investment rate of solar energy projects because of the particular causes of the European energy crisis by the reason of Russia and Ukraine war and escalating risks in DXY and US treasury yields as a result of federal fund rate hikes against inflationary pressures. Solar energy investments are delicate instruments to global oil shocks and higher DXY in controlling Inflation and currency volatility; therefore, resilient policies should solicit the demand because of environmental and economic reasons to reduce the external dependency of Türkiye.

The COVID-19 pandemic affected entire humanity, sustainable development and international trade. Even if international trade is in the recovery phase, COVID-19 pandemic's adverse effects on sustainable development and trade continue to be experienced globally. Furthermore, break out of the war in Ukraine (WIU) further affected not only Ukraine and Russia but also other countries. Countries have started to experience adverse impacts of the WIU more deeply as this war continues. From the global sustainable development and trade perspectives, the WIU impacts' magnitude is affected by the significance of Ukraine and Russia's role in and contribution to the global economy and trade (e.g. agriculture, energy). All countries, including developed, developing and under-developed countries, have started to be affected at different levels due to the adverse impacts of this war. Based on an in-depth literature review, this chapter aims to investigate the WIU's impacts on global sustainable development and international trade. Furthermore, effects of the WIU on climate change and on the fight against climate change are investigated within the scope of this chapter. This chapter is expected to be useful to all stakeholders of sustainable development including politicians and researchers.

This study aims to develop a novel thermal modeling strategy to simulate electron beam powder bed fusion at part scale with machine-varying process parameters strategy. Single-bead and part-scale experiments and modeling were studied. Scanning strategies were described by the process controlling functions that enabled modeling.

The finite element analysis thermal model was used along with the powder bed fusion with electron beam experiments. The proposed strategy involves dividing a part into smaller sections and creating meso-scale models for each subsection. These meso-scale models take into consideration the variable process parameters, including power and velocity of the moving heat source, during part building. Subsequently, these models are integrated to perform partscale simulations, enabling more realistic predictions of thermal accumulation and resulting distortions. The model was built and validated with single-bead experiments and bulky parts with different features.

Single-bead experiments demonstrated an average error rate of 6%–24% for melt pool dimension prediction using the proposed meso-scale models with different scanning control functions. Part-scale simulations for three different geometries (cantilever beams with supports, bulk artifact and topology-optimized transfer arm) showed good agreement between modeled temperature changes and experimental deformation values.

This study presents a novel approach for electron beam powder bed fusion modeling that leverages meso-scale models to capture the influence of variable process parameters on part quality. This strategy offers improved accuracy for predicting part geometry and identifying potential defects, leading to a more efficient additive manufacturing process.