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Figure 13L.1 gives a preview of what’s coming in the form of waveforms at several points. Before you have built the circuits, these waveforms may be a bit cryptic; but trying to understand these plots may help you to get a grip on the whole project. Then we’ll finish these lab notes with some suggestions on how to test your circuits.
In this chapter we meet an amplifier sensitive to a difference between two inputs rather than to a difference from ground. This novelty permits implementation of the hugely important operational amplifier, which from the next class onward will be our principal analog building block.
Surface gravity waves induce a drift on objects floating on the water’s surface. This study presents laboratory experiments investigating the drift of large two-dimensional floating objects on deep-water, unidirectional, regular waves, with wave steepness ranging from 0.04 to 0.31 (0.04 $\lt k{a_w}\lt$ 0.31, where $k$ is the wavenumber and $a_w$ the wave amplitude). The objects were carefully designed to have a rectangular cross-section with a constant aspect ratio; their size varied from 2.6 $\%$ to 27 $\%$ of the incident wavelength. We observed Lagrangian behaviour for small objects. Small and large objects exhibited fundamentally different drift behaviour at high compared with low wave steepness, with a regime shift observed at a certain size and wave steepness. The scaling of object drift with steepness depends on the relative size of the object. For small objects, drift scales with steepness squared, whereas drift becomes a linear function of steepness as the object size increases. For objects that are relatively large but smaller than 13–16% of a wavelength (low to high steepness), we provide experimental evidence supporting the mechanisms of drift enhancement recently identified by Xiao et al. (J. Fluid Mech., vol. 980, 2024, p. A27) and termed the ‘diffraction-modified Stokes drift’. This enhanced drift behaviour, compared with the theoretical Stokes drift for infinitely small fluid parcels, is attributed to changes in the objects’ oscillatory motion and local wave amplitude distribution (standing wave pattern) due to the presence of the object. In the case of larger objects, similar to Harms (J. Waterw. Port Coast. Ocean Eng., vol. 113(6), 1987, pp. 606–622), we relate the critical size at which drift is maximised to their vertical bobbing motion. We determine the domain of validity for both Stokes drift and the diffraction-modified Stokes drift model of Xiao et al. (J. Fluid Mech., vol. 980, 2024, A27) in terms of relative size and wave steepness and propose an empirical parametrisation based on our experimental data.
You now have a working DAC available in your microcontroller. We are going to use the built-in ADC to allow us to digitize analog signals as well. Once you’ve got these peripherals available, it’s fun to try altering waveforms, fun to see the result on a scope and fun to hear the result.
The skeleton code below initializes the DAC, sets up the SysTick timer to provide a 1ms interrupt for the Delay() function and then outputs a sawtooth waveform on Arduino pin A0.
How do high-gain amplifiers, see Fig. 5W.1, compare with respect to “linearity” or constancy of gain over the output swing? Explain your conclusion, briefly. Assume that each amplifier is fed by a properly-biased input.
We use the Golden Rules to calculate gain if, say, we feed back one part in 100. The Golden Rules rely on an assumption that op-amp gain is very high (because, in Black’s words, “… improvements are attained in proportion to the sacrifice that is made in amplifier gain…”).
Construct the parallel resonant circuit shown in Fig. 3L.1. Drive it with a sinewave, varying the frequency through a range that includes what you calculate to be the circuit’s resonant frequency. Compare the resonant frequency that you observe with the one you calculated.
In the previous chapters we used several of the built-in peripherals in the SparkFun SAMD21 Mini including the DAC, the Timer/Counter and the EIC (in a worked example). While modern microcontrollers like the SAMD21 have an impressive selection of internal devices, many systems incorporating a microcontroller require peripherals not available internally or may need to communicate with some external computer or system. To handle access to external devices and systems, most microcontrollers support some form of external communications.
The principal challenge here is simply to get used to the breadboard and the way to connect instruments to it. We do not expect you to find Ohm’s law surprising. Try to build your circuit on the breadboard, not in the air. Novices often begin by suspending a resistor between the jaws of alligator clips that run to power supply and meters. Try to do better: plug the two leads of the DUT (“Device Under Test”) into the plastic breadboard strip.
Now things get a little more complicated, and more interesting, as we meet frequency-dependent circuits. We rely on the capacitor (or just “cap”) to implement this new trick, which depends on the capacitor’s ability to “remember” its recent history.
Then the remainder of the lab is given to trying applications for the so-called analog switch or transmission gate: a switch that can pass a signal in either direction, doing a good job of approximating a mechanical switch – or, more precisely, the electromechanical switch called a relay.
Granular surface flows are frequently encountered in nature as well as during handling of powders in different industries. An experimental study of granular surface flow on a heap is carried out. The heap is formed by pouring nearly monodisperse spherical particles from the rectangular slit orifice of a hopper on a rough rectangular plate. A flow of particles is developed on the heap surface, which is planar in the central region, with particles flowing over the edge of the plate into a collection chamber. The geometry considered in this study is an example of a fully three-dimensional heap without side walls. The surface velocities of the particles are measured using high-speed videography and particle tracking velocimetry for different mass flow rates with steel balls and glass beads of two different sizes, for heaps of different aspect ratios. The flow is uni-directional and fully developed in a central zone on the heap surface. The flowing layer thickness is measured in this zone by immersing a soot-coated blade into the flow. The angle of inclination of the free surface of the heap is found to be nearly constant for a ten-fold increase of the mass flow rate. The scaled flowing layer thickness is found to vary linearly with the scaled flow rate and the data for all the particles collapse to a single line over a ten-fold increase in the scaled flow rate and an increase in the aspect ratio of the heap by a factor of 1.75. The predicted scaled surface velocity and scaled shear rate using this correlation match the measured values.