Reza Shirmohammadi

Bio: Reza Shirmohammadi is an academic researcher from University of Tehran. The author has contributed to research in topics: Exergy & Exergy efficiency. The author has an hindex of 22, co-authored 48 publications receiving 1154 citations. Previous affiliations of Reza Shirmohammadi include Islamic Azad University & University of Zaragoza.

Analysis of hydraulic fracturing techniques: hybrid fuzzy approaches

Abstract: Hydraulic fracturing technologies revolutionize the way petroleum industries drill the conventional and unconventional formations by the purpose for oil recovery enhancement. Multi-criteria decision-making (MCDM) methods are always considered as the preferable techniques in organizational and industrial operational performances that some of them are being widely administered for numerous purposes. The objective of this comprehensive study is to conduct an investigation about the considerable influence of five important criteria on the hydraulic fracturing techniques and select the best technology regarding enhancing oil recovery factor. Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) analyses are applied to compare each criterion. Consequently, among the five fundamental criteria for selecting and operating hydraulic fracturing, in situ stress-strain with the score weight of 0.421 is the most important selectivity criteria. Furthermore, after analyzing the results derived from FAHP and FTOPSIS methods, hydra-jet fracturing and zipper fracturing techniques with the normalized weights of 0.186 and 0.194, and relative closeness coefficients of 0.69 with a 0.66 are considered respectively as the best and optimum techniques of hydraulic fracturing. Last but not least, the cavitation hydro-vibration fracturing and explosive fracturing are the least preferable methods among hydraulic fracturing techniques.

Implementing absorption refrigeration cycle in lieu of DMR and C3MR cycles in the integrated NGL, LNG and NRU unit

Abstract: In this paper, the potential of absorption refrigeration cycle to be replaced by C3MR and DMR cycles and to reduce energy consumption in the integrated structure of NGL, LNG and NRU is investigated. Having simulated and optimized, the absorption refrigeration cycle is replaced by one of the compression cycles in the two presented integrated structures, and the new integrated process with AR-MR1 refrigeration cycle (pre-cooling by absorption refrigeration system and liquefaction by mixed refrigerant) is presented. The new structures are investigated through exergy and economic analyses. The integrated structure of AR-MR1 in comparison with C3MR and DMR processes has reduced the power consumption by about 18.4% and 12.6%, respectively. Sensitivity analysis of economic parameters has been carried out with respect to the utility price as well as effect of product price on the market with respect to the presented structures.

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

Abstract: . Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data and (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange (R2 0.6), gross primary production (R2> 0.7), latent heat (R2 > 0.7), sensible heat (R2 > 0.7), and net radiation (R2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well (R2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted (R2

“Stabilization wedges: Solving the climate problem for the next 50 years with current technologies” from science magazine (2004)

Abstract: Humanity already possesses the fundamental scientific, technical, and industrial know-how to solve the carbon and climate problem for the next half-century. A portfolio of technologies now exists to meet the world's energy needs over the next 50 years and limit atmospheric CO2 to a trajectory that avoids a doubling of the preindustrial concentration. Every element in this portfolio has passed beyond the laboratory bench and demonstration project; many are already implemented somewhere at full industrial scale. Although no element is a credible candidate for doing the entire job (or even half the job) by itself, the portfolio as a whole is large enough that not every element has to be used.