This paper presents a structural–parametric synthesis of the four-link and Stephenson I, Stephenson II, and Stephenson III six-link path-generating mechanisms. The four-link path-generating mechanism is formed by connecting the output point and the base using an active closing kinematic chain (CKC) with two DOFs and a negative CKC of the type RR. The six-link path-generating mechanisms are formed by connecting the output point and the base by active, passive and negative CKCs. Active CKC has active kinematic pair, passive CKC has zero DOF, and negative CKC has a negative DOF. Active and negative CKCs impose geometrical constraints on the movement of the output point, and the geometric parameters of their links are determined by least-square approximation. Geometric parameters of the passive CKC are varied to satisfy the geometrical constraints of the active and negative CKCs. The CKCs of the active, passive and negative types, connecting the output point and the base, are the structural modules from which the different types of the path-generating mechanisms are synthesized. Numerical examples of the parametric synthesis of the four-link and six-link path-generating mechanisms are presented.

This article explores an intelligent control system for a dual-loop solar installation with thermosiphon circulation, designed to improve the efficiency of hot water supply and heating. The proposed system integrates a flat-plate solar collector, a heat exchange loop, a heat pump, a storage tank, circulation pumps, and an AI forecasting module. The main idea of the work is to transition from traditional threshold control to adaptive control based on forecasting the temperature of the collector, the heat transfer fluid, the storage tank, the heat load, and energy consumption. To evaluate the effectiveness of the proposed approach, calculation data were generated for solar radiation, ambient temperature, system temperature conditions, pump operation, thermal efficiency, and energy consumption. The results show that AI control enables the required storage tank temperature of 50 °C to be reached more quickly, reduces the average temperature deviation from 4.2 to 2.6 °C, and increases the average system efficiency from 54.3% to 60.1%. Daily energy consumption decreases from 12.0 to 9.93 kW·h, corresponding to a 17.3% savings, while useful heat output increases from 40.2 to 44.5 kW·h/day. In addition, the number of pump switching cycles decreases from 28 to 17, which reduces the load on the equipment and improves operational reliability. The accuracy of the AI model is confirmed by the MAE, RMSE, MAPE, and R² metrics. The highest accuracy was achieved for predicting the storage tank temperature, where MAE was 0.96 °C, RMSE was 1.27 °C, MAPE was 2.4%, and R² reached 0.97. The results confirm that the use of artificial intelligence improves energy efficiency, temperature stability, and operational reliability of a dual-loop solar system with thermosiphon circulation.

The problem of the structural – kinematical synthesis of the path – generating adjustable spatial mechanisms of the IV class of a kind RRCSSRRS (where R-rotative, C-cylindrical and S-spherical kine-matical pairs ) is considered. It is given by the method of conditional general coordinates the algorithms of the kinematical analysis of the adj ustable spatial mechanisms of the IV class of a kind RRCSSRRS (where R – rotative, C – cylin-drical and S – spherical kinemaric pairs).

This article reviews the development and performance evaluation of a dual-loop solar hot water system featuring a vacuum tube collector, a phase-change heat exchanger, and automated control. The proposed system includes a vacuum solar collector with a multilayer selective coating, a composite capillary tube, a circulation pump with adjustable speed, an ethanol-based phase-change heat exchanger, temperature, pressure, and water level sensors, a microprocessor controller, protection against overheating and freezing, as well as a solar panel for off-grid power supply. The research methodology is based on thermal modelling of solar energy absorption processes, heat transfer in the primary and secondary loops, assessment of heat losses, the efficiency of the phase-change heat exchanger, and the overall system efficiency. The computational analysis was performed for a solar radiation range of 400–1000 W/m². The results show that as solar radiation increases, the useful thermal power rises from 554 to 1546 W, and the collector efficiency increases from 69.3% to 77.3%. The efficiency of the phase-change heat exchanger ranges from 89.9% to 93.0%, confirming stable heat transfer to the secondary loop. Compared to a conventional system, the proposed design provides an increase in collector efficiency from 65% to 77%, an increase in heat exchanger efficiency from 85% to 93%, and a reduction in heat losses from 180 to 108 W, which is approximately 40%. The results obtained confirm the promising application of an integrated dual-loop solar installation for energy-efficient and autonomous hot water supply.

This article discusses a hybrid photovoltaic/thermal PV/T system designed to simultaneously generate electrical and thermal energy using solar radiation. The main focus is on improving the system’s energy efficiency through the use of a CuO-ZnO-based hybrid nanofluid, which serves as the heat transfer fluid in the collector’s thermal circuit. The design of the PV/T module is presented, including a photovoltaic panel, a translucent thermal insulation coating, a chemically coated copper absorbent sheet, copper tubes for heat transfer fluid circulation, and a thermal insulation foundation. A measurement and control scheme is also described, providing monitoring of temperature, solar radiation, flow rate, pressure, voltage, and current. The calculated results show that with an increase in solar radiation from 420 to 980 W/m², the overall efficiency of the PV/T system increases from 42.0% to 54.1%. A comparison of working fluids showed that the CuO-ZnO hybrid nanofluid provides the highest overall efficiency of 57.1%, whereas for water this value is 50.7%. The optimal nanoparticle concentration is 0.5%, at which the best balance between efficiency improvement and pressure drop increase is achieved. The results confirm the potential of using CuO-ZnO nanofluid and an automated control loop to enhance the electrical and thermal performance of hybrid PV/T systems.

Unlike anthropomorphic manipulators, spatial parallel manipulators (SPM) provide specified movements or discrete positions of the end effector with certain fixed geometric parameters of the structural modules (SM) of the SPM. The determination of the fixed geometric parameters, referred to as synthesis parameters, based on the given laws of motion or discrete positions of the end effector and input links, constitutes the synthesis task of the SPM.