Sentence examples for large scale experimental data from inspiring English sources

To address this complex phenomenon, several simple models were developed and tested against large scale experimental data for the past three decades.

An analytic tool is introduced for the evaluation of the fatigue loading of a wind turbine operating in complex terrain, from large scale experimental data.

This paper describes a validation of the EUROPLEXUS code against several large scale experimental data sets in order to improve its hydrogen combustion modeling capabilities in industrial settings (e.g. reactor buildings).

The study was carried out using a 24 factorial design of experiments and the effects of the following variables were investigated based on large scale experimental data: temperature, liquor feed flow rate, pressure and feed air/COG (coke oven gas) ratio.

In this issue, Qiang Huang et al. observed that a lot of biomolecular networks are built from the large scale experimental data produced by the rapidly developing high-throughput techniques as well as literature and other sources.

In the last decade, plenty of biological networks are built from the large scale experimental data produced by high-throughput techniques as well as literature and other sources [ 1- 7].

A rigorous inter-comparison of the codes is performed using large-scale experimental data from the UK Flood Channel Facility for a two-stage meandering channel.

This rapidly changing scenario together with availability of high precision and large-scale experimental data has enabled development of high fidelity simulation tools capable of simulating multi-physics multi-scale phenomena.

Two- and three-dimensional transient numerical simulations of gas/solid flow patterns in circulating and bubbling fluidized beds are presented, along with a comparison of the predicted flow parameters with large-scale experimental data.

Since high-throughput measurement technologies are available, large-scale experimental data from transcriptomics, proteomics, and metabolomics should be supported.

Here we report the development of a novel strategy to explore the biological properties of gene sets found in global collections of public or proprietary large-scale experimental data.