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Borehole thermal energy storage (BTES) represents cutting-edge technology harnessing the Earth’s subsurface to store and extract thermal energy for heating and cooling purposes. Achieving optimal performance in BTES systems relies heavily on selecting the right operational parameters. Among these parameters, charging and discharging flow rates play a significant role in determining the amount of heat that can be effectively recovered from the system. In this study, we introduce a genetic algorithm as an optimization tool aimed at fine-tuning these operational parameters within a baseline BTES model. The BTES model was developed using FEFLOW software and simulated over a 3-year period. After each 3-year simulation, the genetic algorithm iteratively adjusted the operational parameters to attain the optimal configuration for maximizing heat recovery from the BTES system. Additional analysis was conducted to explore the impact of BTES system size and borehole spacing on heat recovery. Results indicate that the genetic algorithm effectively optimized parameters, leading to enhanced heat recovery efficiency. Moreover, the scenario studies highlighted that closer borehole spacing correlates with higher recovery efficiency.

The evolution of complex circuits remains a challenge for the Evolvable Hardware field in spite much effort. There are two major issues: the amount of testing required and the low evolvability of representation structures to handle complex circuitry, at least partially due to the destructive effects of genetic operators. A 64-bit ×64-bit add-shift multiplier circuit modelled at register-transfer level in SystemVerilog would require approximately 33,200 gates when synthesized using Yosys Open SYnthesis Suite tool. This enormous gate count makes evolving such a circuit at the gate-level difficult. We use Grammatical Evolution (GE) and SystemVerilog, a hardware description language (HDL), to evolve fully functional parameterized Adder, Multiplier, Selective Parity and Up–Down Counter circuits at a more abstract level other than gate level—register transfer level. Parameterized modules have the additional benefit of not requiring a re-run of evolutionary experiments if multiple instances with different input sizes are required. For example, a 64-bit ×64-bit and 128-bit ×128-bit multipliers etc., can be instantiated from  a fully evolved functional and parameterized N-bit ×N-bit multiplier. The Adder (6.4×), Multiplier (10.7×) and Selective Parity (6.7×) circuits are substantially larger than the current state of the art for evolutionary approaches. We are able to scale so dramatically because of the use of a HDL, which permits us to operate at a register-transfer level. Furthermore, we adopt a well known technique for reducing testing from digital circuit design known as corner case testing. Skilled circuit designers rely on this to avoid time-consuming exhaustive testing. We demonstrate a simple way to identify and use corner cases for evolutionary testing and show that it enables the generation of massively complex circuits. All circuits were successfully evolved without resorting to the use of any standard decomposition methods, due to our ability to use programming constructs and operators available in SystemVerilog.

Acoustic stethoscopes are used to monitor signals from patients. Incidentally, the connecting tube between the chest-piece and the ear-piece of common stethoscopes is known to serve as a medium for transmitting pathogens from patients to physicians or from one patient to another patient. This work presents a wireless stethoscope design with mobile integration that transmits heart sounds to mobile devices for evaluation and analysis, thus, eliminates the connecting tube. This is an extension of the previous work that presented the proof of concept of a wireless stethoscope with Bluetooth transmission. In this work, however, the chest-piece of the traditional stethoscope is integrated with microcontroller unit and Bluetooth communication device. Captured signals are processed and transmitted wirelessly to a mobile device with interface application software for recording, listening and visual display of waveforms. Following numerical simulation, a prototype was developed. Testing conducted on the prototype device using a class 2 Bluetooth device with 4dBm transmission power showed good quality received signals when the mobile device was placed 20m within indoor environments and 42m in open-space outdoor environment, beyond which degradation in quality occurs. It is worth pointing out that a smart Bluetooth device with high transmission range and data speed may produce much longer operating distance. Hence, for applications that require operating ranges beyond 50m, smart Bluetooth devices may be well suited for such systems. This system may serve as the means for monitoring patients from remote locations particularly quarantine units and can also be useful for training health personnel through broadcasting of recorded signals for analysis and evaluation by members of a medical team.