Drivers, computer

For catastrophic demand-related pump failures, the variability is explained by the following factors listed in their order of importance system application, pump driver, operating mode, reactor type, pump type, and unidentified plant-specific influences. Quantitative failure rate adjustments are provided for the effects of these factors. In the case of catastrophic time-dependent pump failures, the failure rate variability is explained by three factors reactor type, pump driver, and unidentified plant-specific Influences. Point and confidence interval failure rate estimates are provided for each selected pump by considering the influential factors. Both types of estimates represent an improvement over the estimates computed exclusively from the data on each pump. The coded IPRDS data used in the analysis is provided in an appendix. A similar treatment applies to the valve data. 

Fig. 14—A sketch of surface force apparatus. (1) cantilever, (2) samples, (3) supporter and driver for lateral motion, (4) chamber, (5) supporter and driver for normal displacement, (6) lens, (7) prism, (8) spectrometer, (9) computer for data collection.

Tribology performances and applications of ordered molecular films have been a long-standing research subject in SKLT, the workplace for the authors of this book. Hu and Luo [42] prepared SAMs of fluoroalkylsilane (FAS) and poly-fluorealkylmethacrylate (PFAM) on the magnetic head of computer hard disk drivers. Experiment results show that the molecular films greatly improve the performance of the... 

Figure 24.2 Schematic diagram of the setup used to measure and control H2O concentration and gas temperature in the combustion region (in situ) of a forced 5-kilowatt combustor at Stanford University 1 — steel duct 2 — quartz duct 3 — A1 duct 4 — multiplexed beam 5 — tunable diode lasers 6 — data acquisition and control computer 7 — control signals 8 — primary air driver Aair sin(27r/of) 9 — fuel drivers Afuei sin(27r/of-f dfuei) 10 — demultiplexing box 11 — Si detector (ND filter) and 12 — laser beam...

Figure 24.10 Schematic diagram of the combustion-control experiment at China Lake 1 — primary air 2 — primary air driver sin(27r/ot) 3 — pyrolysis gases N2 -h C2H4 4 — secondary air 5 — secondary air drivers sin(27r/ot- -0) 6 — demultiplexing box 7 — sampling probe 8 — multipass fast-sample cell (36-meter path) 9 — InGaAs detector 10 — multiplexed beam and 11 — data acquisition and control computer...

The main driver behind developing LFMM is computational efficiency. Although DFT has undoubtedly revolutionized the theoretical treatment of TM systems, there are many instances where all QM methods, even DFT, are simply not viable. Comprehensive conformational searching, molecular dynamics, and virtual screening represent hundreds of thousands of individual calculations and QM methods are too expensive. We are forced to turn to classical models but, for TM centers, this presents a whole new set of challenges. However, since we cannot easily make QM orders of magnitude faster, our only option is to make MM smarter and thus able to cope with the extra demands of coordination complexes. 

Flyer velocity data for 1-D configurations were used to compute the Gurney constants for the six expls shown in Table 2. Most of the data for PBX 9404, Comp B, and Baratol are from SRI flyer plate experiments, and the other data are largely from LRL. The PWG s are either P-80 s or P-120 s (for the six-inch-thick drivers), and we have assumed the same L for both. 

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