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A three-dimensional heat transfer numerical model is proposed here for the soft-body caterpillar-like robots to present insights for biologists and engineers understanding heat-induced locomotion of these robots.
Prediction of multiple emissions of boiler such as NOX, SO2 and mercury accurately and quickly can help operating engineers understanding the power unit deeply and controlling harmful emissions efficiently.
These lessons learned can help software engineers understanding our proposal of a set of practical activities.
Besides, visualization also enhances the engineers' understanding of the column performance.
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This approach is two-fold: as an AFM-unexperienced user discovering its principle of operation at nanoscale or as a future engineer understanding its multi-disciplinary structure involving mechanics, optics, electronics, software and control sciences.
Overall results suggested that the systematic indices introduced in this study had a clear relationship with pavement performance, so it could be used to assist engineers in many ways such as comparing different load spectra, communicating between engineers, and understanding the relationship between traffic and pavement performance for a specific design at any point in time.
There will also be more telemetry to assist the engineers in understanding the exact sequence of events during the landing.
The results of the analyses can aid engineers in understanding the local and global response of steel moment resisting frames with RBS connection under fire loading.
The identified un-scaled flexibility will reveal the load deflection characteristics of a structure to further engineers׳ understanding about the structure׳s safety condition.
This research demonstrates that the PV simulation model developed during the study is simple, but very helpful to PV system engineers in understanding the I V curves and for accurately predicting PV system power production under outdoor conditions.
The objective of studying software reliability is to assist software engineers in understanding more of the probabilistic nature of software failures during the debugging stages and to construct reliability models.
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