Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

비만아 부모의 돌봄 경험: q 방법론

Challenges and Opportunities for Solar Evaporation

Emerging desalination technologies for water treatment: a critical review.

Enhancing the efficiency of solar still is important for solar stills. In this study, the weighted values of environment factors (descriptors) on the efficiency of solar evaporation are obtained by using a machine learning algorithm, random forest. To verify the advancement between random forest and mathematical data analysis, two traditional methods, pair wise plots and Pearson correlation analysis, are conducted for comparison. Experimental data are obtained from around 100 articles since 2014. The results indicated that traditional methods failed at obtaining reasonable weighted values, while random forest is competent. It is found that thermal design is the most significant descriptors to obtain a high efficiency. The lack of complete dataset is the main challenge for more in-depth and comprehensive analysis. This work may promote the enhancement of production and efficiency of solar stills.

/pdf/the-weighted-values-of-solar-evaporation-s-environment-3mqwv8gn69.pdf

The Weighted Values of Solar Evaporation’s Environment Factors Obtained by Machine Learning

Productivity Modeling Enhancement of a Solar Desalination Unit with Nanofluids Using Machine Learning Algorithms Integrated with Bayesian Optimization

The development and growth in renewable technologies, practically photovoltaic (PV) arrays and wind turbines (WT) have the key role to achieve the worldwide goal towards sustainable energy systems. Hybrid renewable energy system (HRES) can provide safe, eco-friendly and economic solutions for supplying the electrical load demand. This paper developed an autonomous HRES comprising PV, WT, diesel generator, battery, and converter technologies for electrification of an agriculture-isolated area, in Sudan as a real case study. Techno-economic optimization analysis for different hybridization scenarios is performed with a main target to find the most feasible configuration with least cost and harmful emission impact considering technical, economic and environmental perspectives with aid of HOMER Pro software. The results indicate that PV/WT/diesel/battery show the most feasible solution for supplying the investigated area. The system potentially gets the minimum net present cost (NPC) and cost of energy (COE) of 17.6 M$ and 0.283 $/kWh, respectively. In addition, the proposed optimal system achieves around 93.77% reduction in CO 2 emissions as well as 94.14% saving in fuel consumption compared to the diesel-based energy system.

Techno-economic Design and Assessment of Grid-Isolated Hybrid Renewable Energy System for Agriculture Sector

Experimental study of a hemispherical solar distillation system with and without rock salt balls as low-cost sensible storage: Performance optimization and comparative analysis

Swellam W. Sharshir

Papers

The Weighted Values of Solar Evaporation’s Environment Factors Obtained by Machine Learning

Productivity Modeling Enhancement of a Solar Desalination Unit with Nanofluids Using Machine Learning Algorithms Integrated with Bayesian Optimization

Techno-economic Design and Assessment of Grid-Isolated Hybrid Renewable Energy System for Agriculture Sector

Experimental study of a hemispherical solar distillation system with and without rock salt balls as low-cost sensible storage: Performance optimization and comparative analysis

Humidification dehumidification saline water desalination system utilizing high frequency ultrasonic humidifier and solar heated air stream