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This lab is divided into two parts. In the first part everyone will add hardware and Verilog code to implement a four-digit multiplexed seven-segment display. In the second part, you will create something interesting with this display.
Early microcontrollers typically provided only a few built-in peripheral devices in addition to the CPU and memory that made them stand-alone devices. For example, the original version of the 8051 developed by Intel in 1980 included only two 16-bit timer/counters and a serial port (UART), in addition to the basic CPU, memory and I/O ports.
This chapter discusses some primal heuristics that do not necessarily belong with the mainstream methods that have been implemented in the MIP solvers but are interesting either for historical reasons (first attempts of the MIP community to devise heuristic solutions within a general MIP scheme) or because they combine many of the ingredients that are at the core of this book.
In this lab, we would like you to design the control logic for a reaction timer as a Finite State Machine and then implement it in several ways. You will first build the control logic FSM using flip-flops and combinational logic. Then you will replace the combinational logic with a ROM or RAM built from the WebFPGA.
Wave impact on solid structures is a well-studied phenomenon, but almost exclusively for the case that the impacting liquid (e.g. water) is surrounded by a non-condensable gas (such as air). In this study we turn to wave impact in a boiling liquid, a liquid that is in thermal equilibrium with its own vapour, which is of key relevance to the transport of cryogenic liquids, such as liquified natural gas and liquid hydrogen in the near future. More specifically, we use the Atmosphere facility at MARIN, NL, to prepare water/water vapour systems at different temperatures along the vapour curve. Here, we perform wave impact experiments by generating a soliton in a flume contained within the autoclave of the facility. A bathymetry profile interacts with the soliton, leading to a breaking wave that impacts onto a vertical wall, where we measure the pressures occurring during impact by means of $100$ embedded pressure sensors. In boiling liquids, we report wave impact pressures that are up to two orders of magnitude larger than those measured in comparable water–air experiments. We trace these pressures back to the collapse of the entrapped vapour pocket, which we semi-quantitatively describe using a simplified hemicylindrical vapour bubble model, which is in good agreement with the experimental findings. Finally, this allows us to predict the relevance of our findings for the transport of cryogenic liquids in huge overseas carriers where wave impact due to sloshing is the dominant cause of hydrodynamic load of containment systems in cargo tanks.
This circuit, Fig. 16L.1, the most fundamental of flip-flop or memory circuits, can be built with either NANDs or NORs. We will build the NAND form. It is called an SR flip-flop or latch because it can be “Set” or “Reset.” In the NAND form it also is called a “cross-coupled NAND latch.”
In a quiescent medium, chemically active particles propel themselves by emitting or absorbing solutes, creating concentration gradients that induce a slip at the particle surface. This self-propulsion occurs when solute advection overcomes diffusion. However, an imposed flow field can alter these dynamics. This study explores the propulsion characteristics and the related rheological consequences of chemically active particles in an imposed uniaxial extensional flow analytically and numerically. An asymptotic solution is obtained for weak imposed flow relative to self-induced diffusiophoretic slip. Meanwhile, finite element simulations are carried out over a wide range of imposed flow strength and Péclet number. The results reveal that the interplay between solute advection, imposed flow and diffusiophoretic slip significantly affects particle propulsion and suspension rheology. While solute advection and diffusiophoretic slip tend to create asymmetric solute distributions, promoting self-propulsion, imposed extensional flow promotes symmetric distributions, hindering self-propulsion. This not only delays the start of self-propulsion but also results in an early transition from a propulsion state to a stationary state characterised by an abrupt halt at relatively lower Péclet number compared to a quiescent medium. Post the abrupt halt, a stirring effect induced by particle activity and imposed extensional flow results in an increased magnitude of stresslet, thus a sudden change in the effective viscosity of the active suspension. The effect of imposed extensional flow on active particle dynamics and suspension rheology can be described succinctly by categorising the overall dynamics into three separate regimes, determined by the Péclet number and the intensity of the extensional flow.
The acoustofluidic method holds great promise for manipulating micro-organisms. When exposed to the steady vortex structures of acoustic streaming flow, these micro-organisms exhibit intriguing dynamic behaviours, such as hydrodynamic trapping and aggregation. To uncover the mechanisms behind these behaviours, we investigate the swimming dynamics of both passive and active particles within a two-dimensional acoustic streaming flow. By employing a theoretically calculated streaming flow field, we demonstrate the existence of stable bounded orbits for particles. Additionally, we introduce rotational diffusion and examine the distribution of particles under varying flow strengths. Our findings reveal that active particles can laterally migrate across streamlines and become trapped in stable bounded orbits closer to the vortex centre, whereas passive particles are confined to movement along the streamlines. We emphasise the influence of the flow field on the distribution and trapping of active particles, identifying a flow configuration that maximises their aggregation. These insights contribute to the manipulation of microswimmers and the development of innovative biological microfluidic chips.
The power used in a CMOS circuit is directly proportional to clock frequency. Current only flows into or out of a CMOS gate to charge or discharge the input gate-to-source capacitance when the input switches from low to high or visa-versa.
To do all of today’s lab is a challenge: the op-amp circuit is the most complex that you’ve built so far, and if some stage holds you up, you’re likely to run out of time. But that shouldn’t worry you. Only the differential amp (§5L.1) – not its conversion into an op-amp – is fundamental.
We have advertised the differential amp as just a pair of common-emitter amplifiers, and have promised you that there’s not much new to understand here: you can use what you know from the two earlier labs where you build C–E amps. But students have noticed some effects that are new: not what one might expect from experience with a single C–E amp.
Today we look first at one more benign use of positive feedback, an active filter, and then spend most of our time with circuits that oscillate when they should not. In this lab, of course, they “should,” in the sense that we want you to see and believe in the problem of unwanted oscillations. On an ordinary day, the oscillations that these circuits can produce would be undesirable, and would call for a remedy. Some of you have met these so-called “parasitic oscillations” in earlier labs.
A student asked a good, hard question, recently. I was stumped, till the answer struck me – more or less the way the apple is said to have bonked Newton on the head – next morning as I cycled to work.
The integration of machine learning models within MIP computation has been an exciting research trend in the last decade. This chapter reviews the use of such models in conjunction with primal heuristics for MIP.