Global warming is a thermodynamic problem. When excess heat is added to the climate system, the land warms more quickly than the oceans due to the land’s reduced heat capacity. The oceans have a greater heat capacity because of their higher specific heat and the heat mixing in the upper layer of the ocean. Thermodynamic Geoengineering (TG) is a global cooling method that, when deployed at scale, would generate 1.6 times the world’s current supply of primary energy and remove carbon dioxide (CO₂) from the atmosphere. The cooling would mirror the ostensible 2008–2013 global warming hiatus. At scale, 31,000 1-gigawatt (GW) ocean thermal energy conversion (OTEC) plants are estimated to be able to: a) displace about 0.8 watts per square meter (W/m²) of average global surface heat from the surface of the ocean to deep water that could be recycled in 226-year cycles, b) produce 31 terawatts (TW) (relative to 2019 global use of 19.2 TW); c) absorb about 4.3 Gt CO₂ per year from the atmosphere by cooling the surface. The estimated cost of these plants is $2.1 trillion per year, or 30 years to ramp up to 31,000 plants, which are replaced as needed thereafter. For example, the cost of world oil consumption in 2019 was $2.3 trillion for 11.6 TW. The cost of the energy generated is estimated at $0.008/KWh.

Conversion of the ocean’s vertical thermal energy gradient to electricity via OTEC has been demonstrated at small scales over the past century. It represents one of the planet’s most significant (and growing) potential energy sources. As described here, all living organisms need to derive energy from their environment, which heretofore has been given scant serious consideration. A 7th Law of Thermodynamics would complete the suite of thermodynamic laws, unifying them into a universal solution for climate change. 90% of the warming heat going into the oceans is a reasonably recoverable reserve accessible with existing technology and existing economic circumstances. The stratified heat of the ocean’s tropical surface invites work production in accordance with the second law of thermodynamics with minimal environmental disruption. TG is the OTEC improvement that allows for producing two and a half times more energy. It is an endothermic energy reserve that obtains energy from the environment, thereby negating the production of waste heat. This likewise reduces the cost of energy and everything that relies on its consumption. The oceans have a wealth of dissolved minerals and metals that can be sourced for a renewable energy transition and for energy carriers that can deliver ocean-derived power to the land. At scale, 31,000 one-gigawatt (1-GW) TG plants are estimated to displace about 0.9 W/m² of average global surface heat into deep water, from where, at a depth of 1000 m, unconverted heat diffuses back to the surface and is available for recycling.

The present work conducts a comprehensive thermodynamic analysis of a 150 MW_e Integrated Gasification Combined Cycle (IGCC) using Indian coal as the fuel source. The plant layout is modelled and simulated using the “Cycle-Tempo” software. In this study, an innovative approach is employed where the gasifier's bed material is heated by circulating hot water through pipes submerged within the bed. The analysis reveals that increasing the external heat supplied to the gasifier enhances the hydrogen (H₂) content in the syngas, improving both its heating value and cold gas efficiency. Additionally, this increase in external heat favourably impacts the Steam-Methane reforming reaction, boosting the H₂/CH₄ ratio. The thermodynamic results show that the plant achieves an energy efficiency of 44.17% and an exergy efficiency of 40.43%. The study also identifies the condenser as the primary source of energy loss, while the combustor experiences the greatest exergy loss.

The efficiencies and performance of gas turbine cycles are highly dependent on parameters such as the turbine inlet temperature (TIT), compressor inlet temperature (T1), and pressure ratio (Rc). This study analyzed the effects of these parameters on the energy efficiency, exergy efficiency, and specific fuel consumption (SFC) of a simple gas turbine cycle. The analysis found that increasing the TIT leads to higher efficiencies and lower SFC, while increasing the To or Rc results in lower efficiencies and higher SFC. For a TIT of 1400 ℃, T1 of 20 ℃, and Rc of 8, the energy and exergy efficiencies were 32.75% and 30.9%, respectively, with an SFC of 187.9 g/kWh. However, for a TIT of 900 ℃, T1 of 30 ℃, and Rc of 30, the energy and exergy efficiencies dropped to 13.18% and 12.44%, respectively, while the SFC increased to 570.3 g/kWh. The results show that there are optimal combinations of TIT, To, and Rc that maximize performance for a given application. Designers must consider trade-offs between efficiency, emissions, cost, and other factors to optimize gas turbine cycles. Overall, this study provides data and insights to improve the design and operation of simple gas turbine cycles.

This research introduces a novel framework integrating stochastic finite element analysis (FEA) with advanced circular statistical methods to optimize heat pump efficiency under material uncertainties. The proposed methodologies and optimization focus on balancing the mean efficiency and variability by adjusting the concentration parameter of the Von Mises distribution, which models directional variability in thermal conductivity. The study highlights the superiority of the Von Mises distribution in achieving more consistent and efficient thermal performance compared to the uniform distribution. We also conducted a sensitivity analysis of the parameters for further insights. The results show that optimal tuning of the concentration parameter can significantly reduce efficiency variability while maintaining a mean efficiency above the desired threshold. This demonstrates the importance of considering both stochastic effects and directional consistency in thermal systems, providing robust and reliable design strategies.