Design, manufacture and experimental investigation of a thermal conductivity measurement aparatus for liquids

Bu çalışmada, sıvıların ısı iletim katsayısını ölçebilmek amacıyla silindirik metoda göre ölçüm yapan laboratuar tipi cihaz tasarımı yapılmış ve deneysel olarak test edilmiştir. Cihazın doğruluğu, ısı iletim katsayısı bilinen saf su ile 10-40 °C sıcaklık aralığında yapılan deneylerle test edilmiştir. Saf su ile yapılan deneylerden elde edilen sonuçlara göre, ölçülen sıcaklık değerlerinden hesaplanan ısı iletim katsayısı ile fiziksel özellik tablosundan alınan değerler arasındaki maksimum bağıl hata % 13.4, ortalama bağıl hata ise % 7.6 olmuştur. Saf su ile yapılan test deneyleri şartlarında, farklı oranlarda saf su-antifriz karışımı, antifriz ve tuzlu su çözeltisinin ısı iletim katsayılarını belirleyebilmek amacıyla deneyler yapılmış, saf suda olduğu gibi deney sonuçlarına göre ısı iletim katsayıları hesaplanmıştır. Hesaplanan değerlerin regresyon analizi yapılarak, ısı iletim katsayıları sıcaklığın ve saf su içerisindeki madde miktarının fonksiyonu olarak ifade edilmiştir.In this study, a laboratory type device was designed and tested experimentally to measure the thermal conductivity of liquids according to the cylindrical method. The accuracy of the device are tested with pure water experiments at temperatures between 10 and 40 °C. According to obtained results from the pure water experiments, the maximum relative error and mean relative error between the calculated results and the thermo physical table values was about 13.4 % and 7.6 %, respectively. After the accuracy of the device is tested, experiments are repeated using various mixtures of pure water and anti-freeze, anti-freeze only, and salty water solution at the same conditions as pure water experiments. According to the experimental results the thermal conductivity were calculated as pure water. Regression analysis of calculated thermal conductivity values were made and expressed as a function of temperature and substance content in the pure water

Prediction of thermal conductivity of ethylene glycol-water solutions by using artificial neural networks

The objective of this study is to develop an artificial neural network (ANN) model to predict the thermal conductivity of ethylene glycol-water solutions based on experimentally measured variables. The thermal conductivity of solutions at different concentrations and various temperatures was measured using the cylindrical cell method that physical properties of the solution are being determined fills the annular space between two concentric cylinders. During the experiment, heat flows in the radial direction outwards through the test liquid filled in the annual gap to cooling water. In the steady state, conduction inside the cell was described by the Fourier equation in cylindrical coordinates, with boundary conditions corresponding to heat transfer between the solution and cooling water. The performance of ANN was evaluated by a regression analysis between the predicted and the experimental values. The ANN predictions yield R2 in the range of 0.9999 and MAPE in the range of 0.7984% for the test data set. The regression analysis indicated that the ANN model can successfully be used for the prediction of the thermal conductivity of ethylene glycol-water solutions with a high degree of accuracy.Thermal conductivity Ethylene glycol-water solutions Artificial neural network

Performance Assessment of a Novel Solar and Biomass-Based Multi-Generation System Equipped with Nanofluid-Based Compound Parabolic Collectors

The current paper proposes a novel multi-generation system, integrated with compound parabolic collectors and a biomass combustor. In addition to analyzing the comprehensive system in a steady state, the feasibility of using nanofluids as heat transfer fluids in the solar cycle and their effect on the overall performance of the system was studied. The multi-generation system is generally designed for generating electricity, cooling, freshwater, drying, hot water, and hydrogen, with the help of six subsystems. These include a double stage refrigeration system, an organic Rankine cycle, a steam Rankine cycle, a dryer, a proton exchange membrane electrolyzer, and a multistage flash distillation system. Two types of nanoparticles (graphene, silver), which have various high-quality properties when used within ethylene glycol, were chosen as absorbing fluids in the solar cycle. The performance parameters of the base case thermodynamic analysis and some of the variable parameters were calculated, and their effect on system performance was determined. According to the results, a spike in solar irradiation, ambient temperature, output temperature of biomass combustor and nanofluids’ concentration positively affected the overall system performance. The results also clearly showed an improvement in system performance when using nanofluids as working fluids in solar collectors