Optimal Parameters Research Articles

A comprehensive analytical and computational assessment of soil water characteristics curves in Atlantic Canada: Application of a novel SelectKbestbased GEP model

For sustainable agriculture, irrigation is one of the most important management practices in a semi-arid climate. Determining the site-specific soil type-based irrigation water requirements requires the development of a soil water characteristics curve (SWCC). This study focuses on exploring the suitability of analytical SWCC models based on the observed data of SWCC developed using the pressure membrane apparatus. A novel SelectKbest gene expression programming (GEP) model is used to create the generalized machine learning SWCC model for Atlantic Canadian soils. The composite soil samples with representative soil textures of loamy sand, loam, and sandy loam are collected from the selected locations in Prince Edward Island and New Brunswick provinces of Canada. The suitability of models at three regions shows that at all sites, including PEI-1 (loam soil) 1, PEI-2 (loamy sand), and NB-3 (sandy loam) if SWCC data has four measured suction potential levels, then McBee & Bomb and Tani exponential models may be selected. Van Genuchten, double exponential, Ruso, Kosuki, and Gardner's four parameters models should be a good choice for five-section potential. Similarly, for six measured suction potential values, the Fredlund & Xing, Omuto, and Van Genuchten models having parameters should be selected for determining the optimum soil hydraulic parameters. The HydroMe program with Brooks and Corey, four, and five parameters Van Genuchten models performed well. The HydroMe program is calibrated and validated with standard RETC for selected regions of Atlantic Canada, which suggests that the HydroMe program is flexible in developing efficient agricultural water management algorithms. Various performance metrics like R2 and RMSE are employed to assess the robustness of the model. A generalized SWCC model (R2=0.976 and RMSE=0.04) is developed using a novel SelectKbest-based GEP modeling approach for Atlantic Canadian soils. These novel approaches can significantly improve site-specific agricultural water management and decision support systems.

Optimizing FDM process parameters: predictive insights through taguchi, regression, and neural networks

Fused deposition modelling (FDM) is a popular additive manufacturing process used for rapid prototyping and the production of complex geometries. Despite its popularity, FDM’s susceptibility to variations in numerous process parameters can significantly impact the quality, design, functionality, and mechanical properties of 3D printed parts. This study explores thirteen FDM process parameters and their influence on the mechanical properties of polylactic acid (PLA) polymer, encompassing surface roughness, warpage, tensile and bending strength, elongation at break, deformation, and microhardness. The optimum parameters were identified alongside key contributors by applying the Taguchi method, signal-to-noise ratios, and analysis of variances (ANOVA). Notably, specific FDM parameters significantly affect the surface profile, with layer thickness contributing 32.65% and fan speed contributing 8.59% to the observed variations. Similarly, warping values show notable influence from nozzle temperature (29.53%), wall thickness (16.74%), layer thickness (16.56%), and retraction distance (12.80%). Tensile strength is primarily determined by wall thickness (31.83%), followed by infill percentage (26.73%) and infill pattern (16.18%). Elongation at break predominantly correlates with wall thickness (44.82%), with a supplementary contribution from nozzle temperature (10.90%). Microhardness lacks a dominant parameter. Bending strength variations primarily arise from layer thickness (38%), wall thickness (37.6%), and infill percentage (9.17%). Deformation tendencies are influenced by layer thickness (19.20%), print speed (11.37%), wall thickness, and fan speed (10.9% each). The optimized dataset of FDM process parameters was then employed in two prediction models: multiple-regression and artificial neural network (ANN). Evaluation based on the correlation coefficient (R2) and root mean squared error (RMSE) indicates that the ANN model outperforms the multiple-regression approach. The results indicate that precise control of FDM parameters, coupled with ANN predictions, facilitates the fabrication of 3D printed parts with the desired mechanical characteristics.

Comparative adsorption of cationic and anionic dye by using non-activated Black Plum seed biochar for aquatic phase: Isotherm, kinetic and thermodynamic studies

Industrial dye effluents play a major role in water pollution. Textile and leather industries are one of the important sectors that pollute the water by discharging many harmful cationic and anionic dyes during the dyeing process. This study aims to compare the dye removal efficiency of Black Plum seed biochar for the cationic and anionic dyes. The non-activated biochar was prepared through pyrolysis of Black Plum seed powder at 5700 C. The sample's surface chemistry was understood using various characterization techniques like Field Emission Scanning Electron Microscopy (FESEM), Energy-dispersive X-ray spectroscopy (EDS), Brunauer-Emmett-Teller (BET), X-ray diffraction (XRD), Raman-Spectroscopy and Zeta-potential. The experiments were successfully performed by conducting a batch adsorption study at different parameters such as pH, concentration, contact time and temperature. The coefficients of different isotherms and kinetics models were evaluated for non-linear study and the thermodynamic model was also applied. The maximum adsorption capacity was obtained as 42.39 mg/g for Crystal Violet (CV) dye and 6.22 mg/g for Eosin Blue (EB) dye by using the Langmuir isotherm model. Hence, the Black Plum seed biochar (BPSB) has superior adsorption capacity for the cationic dye CV ( removal - 98%) as compared to the anionic dye EB ( removal - 65%) at optimum parameters. Therefore, it is concluded that the BPSB is a natural toxin-free biosorbent and it can be used for the remediation of dyes from industrial wastewater.

Optimal design of chevron braced friction damper for mainshock–aftershock vulnerability control

This study proposes the optimum design of chevron braced friction dampers (CBFDs) for the vulnerability control of steel moment–resisting frames (SMRFs) under mainshock-aftershock (MS-AS) sequences. First, the optimum parameters of the CBFD systems installed in the stories of an inelastic SMRF are found through minimizing the maximum damage index of stories averaged over seven scaled earthquake excitations. The uniform distribution of the story damage along the height of the controlled SMRF is adopted as constraint in the optimization procedure. The damage index is calculated based on the Park-Ang damage model which is expressed based on a linear combination of deformation, moment, and absorbed hysteretic energy of structural elements imposed by an earthquake excitation. Results reveal that the optimized CBFDs-equipped SMRF exhibits better distribution of the story damage than that of the uncontrolled SMRF. Finally, the vulnerability assessment of the optimized CBFDs-equipped SMRF under MS and MS-AS ground motions is investigated by the fragility curves. The fragility assessment emphasize that the optimized CBFDs effectively mitigate the seismic vulnerability of the controlled SMRF under MS-AS sequences at different damage states.

Development of trench-shaped microstructure thermal neutron detector using α-Al2O3:C based on optically stimulated luminescence

Optical stimulated luminescence technique is increasingly used in neutron personal dosimetry, due to its capability of fast readout and potential for re-estimation of absorbed dose. The design configuration and performance of the microstructure optically stimulated luminescence neutron detector (MOSLND) using α-Al2O3:C was reported. To improve thermal neutron response, the MOSLND is structured with a matrix of microstructure trenches into the α-Al2O3:C substrate and backfilled with 6LiF. To obtain an optimum trench geometric parameter, several Monte Carlo simulations were performed using Geant4 code. The simulation results show that relatively high energy deposition can be realized for small cell dimensions with deep trenches, and is significantly increased compared with that of simple planar designs. Based on the results of calculation and practical limitation, the device was produced and tested using D2O-modrated 252Cf. The optimized minimal detectable dose (MDD) corresponding to signal integration time of 2 s is 7.2 μSv. The experimental results indicate that MOSLND can be a potential solution for personal neutron dosimetry.

Optimization of Process Parameters for Microwave Drying of Yellow- and Purple-Fleshed Potatoes

AbstractThe main objective of the present work was to study the optimization of microwave drying of potatoes that have different flesh colors. The effects of independent variables of microwave power (300, 450, 600 W), slice thickness (2–4, 6 mm), and steam blanching time (2, 5, 8 min) on the color, total phenolic content (TPC), antioxidant activity, starch ratio, and total monomeric anthocyanin content (TMA) were investigated by using the Response Surface Methodology (RSM). Before drying, potato slices that had different thicknesses were blanched in steam at 90 °C for indicated times. Optimization was applied to improve bioactive compounds, starch ratio, and color. The optimum drying parameters were determined as 300 W, 6 mm, and 8 min for purple-fleshed potatoes, and 450 W, 6 mm, and 2 min for yellow-fleshed potatoes. This study is beneficial to the development of the processing of potatoes in the food industry and provides more insights into the application of microwave drying technology.

Destruction of n-hexane from the air stream by pulsed discharge plasma: Modelling and key process parameters optimization by CCD-RSM

In this study, a Dielectric-Barrier Discharge (DBD) plasma reactor was used for the degradation of n-hexane from an air stream. a Central Composite Design (CCD) based Response Surface Methodology (RSM), (CCD-RSM) was utilized to explore the effects of experimental parameters including discharge voltage, initial concentration, gas flow rate, relative humidity and their interactions on the reactor performance. The proposed optimization model showed a satisfactory correlation between the predicted and actual results. According to the results, discharge voltage was the most significant parameter affecting the removal efficiency, CO2 selectivity and the level of O3 and NOx formation, whereas energy yield was mainly influenced by gas flow rate and initial concentration. At optimized conditions (discharge voltage of 8.5 kV, inlet concentration of 94.3 ppm, relative humidity of 55 % and gas flow rate of 733.16 ml/min with combined desirability of 0.921), removal efficiency of 92.57 %, CO2 selectivity of 58.87 %, energy efficiency of 0.25 g/kWh, O3 formation of 140.88 mg/m3 and NOx formation of 122.46 ppm were obtained. Water vapour significantly increased the removal efficiency and CO2 selectivity as well as reduced O3 and NOx. The results revealed that the CCD-RSM provided the optimum process parameters for the Non-Thermal Plasma (NTP) system.

Trajectory Tracking Algorithm Study of Coal Mine Water Detector Drilling Bar Installation

Mechanical water detection is recognized as the most reliable and safe production technology for coal mines, mainly for the detection of water hazards in pre-mining operations. Intelligent water detectors are currently the main research direction in mechanical water detection, and the automatic installation of drilling bars is the key to achieving intelligent water detection. Improving the connection accuracy in the process of installing drilling bars is an important research topic for the improvement of control links. To improve the connection accuracy of the drilling bars at the time of supplying material, we used the modified Denavit–Hartenberg method to analyze the motion gestures of the supplied material device and the Lagrange equation to establish a dynamic analysis model. We aimed at better control precision by improving the sliding mode control algorithm and at increasing the convergence rate of tracking errors with a sliding controller based on an exponential approximation law and using saturated functions instead of the symbol functions in the reaching law to weaken the vibration in the control process. We then used particle swarm optimization (PSO) to find the optimum combination parameters of the sliding mode controllers and test the performance of the sliding mode controllers before and after PSO with MATLAB/Simulink. The results showed that the optimized controller has a strong resistance to parameter fluctuations, and the system responds quickly, achieves a good performance, and improves the convergence rate of tracking errors.

Improvement of the oxidative stability of edible oils through enzymatic esterification with hydroxytyrosol‐rich extract

AbstractOxidative degradation is a common issue of commercial edible oils that results in rancidity, downgrading the organoleptic characteristics of food matrices. The aim of this study was the enzymatic modification of common vegetable oils (pomace olive and sunflower oil) with polyphenolic extract to prepare functional oils enriched with bioactive phenolipids. Under that scope, an agro‐industrial effluent, olive mill wastewater, was used as source to recover phenolic compounds. The recovery of hydroxytyrosol and tyrosol reached up to 81.2% ± 0.3% and 98.3% ± 0.2%, respectively. Further, immobilized lipase was used to catalyze the one‐step acylation of these phenolic antioxidants into the oils with the aim of enhancing their stability under accelerated oxidation conditions. The optimum parameters of the bioconversion were found to be 0.1% (w/w) immobilized lipase, 24h of incubation at 50°C under orbital shaking reaching high conversion yields for both phenolic compounds (≥94%). The results also highlighted that the extract‐modified oils presented notable thermooxidative stability at 60°C for 28 days compared to the control and synthetic antioxidant‐enriched oils, as demonstrated by several analytical (conjugated dienes, thiobarbituric reactive substances), chromatographic (solid‐phase microextraction gas chromatography/mass spectroscopy), and spectroscopic (fluorescence, attenuated total reflectance) techniques, giving new insights regarding the preservation of edible oils.Practical Application: Htyr has recently gained much attention as an active ingredient of food matrices for industrial applications due to its high antioxidant/antiradical activity. A major drawback of Htyr exploitation is the high market price and its solubility. Meanwhile, several edible oils are prone to autooxidation during transport, stock management, and household storage. The proposed one‐step biocatalytic process aims to enhance the lipophilicity and bioactivity of Htyr in bulk oil systems, making the use of this potent antioxidant compound feasible. This approach shows promise in extending the shelf life of common oils and highlights the advantages of by‐product management. Moreover, these functional oils can be applied for the preparation of sauces, bakery products, food supplements, and so on, as the bioactive ingredients that are present in them can delay the oxidative cascade reactions and, thus, the spoilage of the products, whereas the whole process meets the requirements of circular economy and green chemistry.

Optimization of Hypericum Perforatum Microencapsulation Process by Spray Drying Method

Hypericum perforatum (HP) contains valuable and beneficial bioactive compounds that have been used to treat or prevent several illnesses. Encapsulation technology offers protection of the active compounds and facilitates to expose of the biologically active compounds in a controlled mechanism. Microcapsulation of the hydroalcoholic gum arabic and maltodextrin have hot been used as wall materials in the encapsulation of HP extract. Therefore, the optimum microencapsulation parameters of Hypericum perforatum (HP) hydroalcoholic extract were determined using response surface methodology (RSM) for the evaluation of HP extract. Three levels of three independent variables were screened using the one-way ANOVA. Five responses were monitored, including total phenolic content (TPC), 2,2-Diphenyl-1-picrylhydrazyl (DPPH), carr index (CI), hausner ratio (HR), and solubility. Optimum drying conditions for Hypericum perforatum microcapsules (HPMs) were determined: 180 °C for inlet air temperature, 1.04/1 for ratio of maltodextrin to gum arabic (w/w), and 1.98/1 for coating to core material ratio (w/w). TPC, antioxidant activity, CI, HR, and solubility values were specified as 316.531 (mg/g GAE), 81.912%, 6.074, 1.066, and 35.017%, respectively, under the optimized conditions. The major compounds of Hypericum perforatum (hypericin and pseudohypericin) extract were determined as 4.19 μg/g microcapsule and 15.09 μg/g microcapsule, respectively. Scanning electron microscope (SEM) analysis revealed that the mean particle diameter of the HPMs was 20.36 µm. Based on these results, microencapsulation of HPMs by spray drying is a viable technique which protects the bioactive compounds of HP leaves, facilitating its application in the pharmaceutical, cosmetic, and food industries.Graphical

Parametric optimisation of laser welding of stainless steel 316L

This paper presents numerical and experimental studies focused on the optimisation of laser welding parameters for AISI 316L stainless steel. The focus of the numerical studies was to obtain the mathematical model with the least time complexity and the highest fidelity. Based on the comparison of different mathematical models, a combination of two models, double ellipsoidal and conical models, was found to be optimal for the numerical simulation of the laser welding process. The studies were also complemented by material characterization studies for validation purpose. A pulse duration of 8 milliseconds and a current of 400 amperes with an average power of 380W were found to be the optimum parameters for laser welding of standard gauge 12 sheet of stainless steel AISI 316L. In addition, the effect of duty factor of the pulsed laser beam on the weld profile was also investigated and was found to be a major contributor to the optimisation process. The properties of the sample welded with the optimised set of parameters were also compared with the base metal, and based on the mechanical characterisation studies, it was found that the yield strength and hardness of the welded sample were improved, but the overall ductility was slightly reduced as compared to the base metal. The average weld zone size was also reduced by increasing the power density due to multiple reflections of the beam.

Extracellular synthesis of heteroatom doped copper oxide nanoparticles from electronic waste – Transforming waste to resource for the remediation of nitrophenol contaminated water

Industrial effluents containing hazardous phenolic compounds such as 4-nitrophenol (4-NP) can threaten aquatic ecosystems and the environment. To address the environmental issues due to nitrophenol-contaminated industrial effluents and rapidly generating electronic waste (e-waste), catalytic nanoparticles are biosynthesized utilizing the waste printed circuit boards (WPCBs) and the cell-free supernatant (CFS) of the bacteria Alcaligenes aquatilis for the catalytic reduction of 4-NP with sodium borohydride (NaBH4). The optimum synthesis parameters to maximize 4-NP reduction were an initial pH of 12.4 and a volume ratio of metal leachate to CFS of 1:3. These nanoparticles were found to be heteroatom-doped CuO/Cu2O (Bio-CuO/Cu2O-PCB) with spherical shape, average crystallite size of 19 nm and average particle size of 19.2 nm. The biosynthesized nanoparticles exhibited excellent catalytic activity in the reduction of 4-NP with a pseudo-first-order rate constant (kapp) of 0.526 min-1, induction period of 2 min, and 90% reduction of 4-NP in 6 min. This work demonstrates the recovery of metal resources from waste as nanoparticles with excellent catalytic activity using a green, eco-friendly synthesis method under ambient conditions. Bio-CuO/Cu2O-PCB showed better activity than commercial CuO, biosynthesized and chemically synthesized CuO using precursor salt. The developed synthesis method is eco-friendly and could yield a recyclable catalyst for reducing harmful aromatic pollutants such as 4-NP present in wastewater to 4-aminophenol, a pharmaceutical intermediate.

SPH-based numerical modelling and performance analysis of a heaving point absorber type wave energy converter with a novel buoy geometry

Heaving point absorber (HPA) is one of the most promising technologies to absorb wave energy. Accordingly in this work, performance of a HPA in terms of capture-width-ratio (CWR) under the effect of hydrodynamics forces were analysed using the SPH-based open-source package: DualSPHysics. 395 cases of simulations, which include five different geometries with different densities of the buoy, different buoy height to wave height ratios, and damping coefficients of the WEC over a range of wave frequencies were studied and optimum operational parameters were found for the novel buoy geometry named: “Super cuboid”. Compared to other geometries, it produced up to 23 % of efficiency increment over a wide range of operational conditions. Furthermore, the flow patterns and pressure variation around different buoy geometries were studied and found that an increase in the projected area of the buoy in vertical direction tends to increase the pressure force which results in increase of CWR. The CWR is also slightly enhanced by the bottom shape of the buoy. Hence it is expected that the use of this novel buoy shape, will contribute to the design of more sustainable and reliable WECs in the future.

Optimum Parameters in Ultrasound Coherent Plane Wave Compounding for High LPWV Estimation: Validation on Phantom and Feasibility in 10 Subjects.

The aim of this study is to determine the optimum and fine values of the number and transmission angles of tilted plane waves for coherent plane-wave compounding (CPWC)-based high local pulse wave velocity (LPWV) estimation. A Verasonics system incorporating a linear array probe L14-5/38 with 128 elements and a pulsatile pump, CompuFlow1000, were used to acquire radio frequency data of 3, 5, 7, and 9 tilted plane wave sequences with angle intervals from 0° to 12° with a coarse interval increment step of 1°, and the angle intervals from 0° to 2° with a fine interval increment step of 0.25° from a carotid vessel phantom with the LPWV of 13.42 ± 0.90 m/s. The mean value, standard deviation, and coefficients of variation (CV) of the estimated LPWVs were calculated to quantitatively assess the performance of different configurations for CPWC-based LPWV estimation. Ten healthy human subjects of two age groups were recruited to assess the in vivo feasibility of the optimum parameter values. The CPWC technique with three plane waves (PRF of 12 kHz corresponding to a frame rate of 4000 Hz) with an interval of 0.75° had LPWVs of 13.52 ± 0.08 m/s with the lowest CV of 1.84% on the phantom, and 5.49 ± 1.46 m/s with the lowest CV of 12.35% on 10 subjects. The optimum parameters determined in this study show the best repeatability of the LPWV measurements with a vessel phantom and 10 healthy subjects, which support further studies on larger datasets for potential applications.

Graphene oxide-based stationary phase synthesis and separation of drug molecules for liquid chromatography (HPLC) analysis

A new graphene oxide-based liquid chromatography stationary phase was synthesized, characterized, and used for the first time in the separation of paracetamol and caffeine in pharmaceutical preparations under reversed phase conditions. For this purpose, graphene oxide was synthesized using the modified Hummers method, and Si-GO stationary phase was obtained by immobilizing graphene oxide on aminopropyl silica. The obtained graphene oxide, Si–GO and aminopropyl silica materials were characterized by XRD, SEM, TEM and FTIR analysis. Different mobile phases were used to separate drug molecules in order to determine the mechanism of interaction between drug molecules and the stationary phase. Once the appropriate solvent system was determined, optimum chromatographic parameters such as mobile phase composition (methanol percentage in water), flow rate and column temperature were determined. The linearity of the method was in the range of 0.989–0.997. The maximum relative standard deviation (% RSD) value was calculated as 0.54. Mean recoveries for paracetamol and caffeine were 98%–99%, respectively, and LOD and LOQ were 6 × 10−3 to 6.5 × 10−3 mg/L and 2 × 10−2 to 2.2 × 10−2 mg/L, respectively. The results showed that the new graphene oxide-based stationary phase could be used for the separation of paracetamol and caffeine in pharmaceutical preparations.

Thermo‐mechanical properties and optimization of sodium alginate as a polymer backbone substrate for biosensor application

AbstractThis study was aim to optimize the formulation of the sodium alginate biosensor substrate with incorporation of sodium alginate (1%‐6%(w/v)) as a polymer backbone and glycerol (10–50 wt%) as a plasticizer. The effect of their interaction on film's tensile strength (TS) and elongation at break (EB) were analyzed via response surface methodology‐central composite design (RSM‐CCD). The optimum parameter of the films for the maximum TS was at 1.90%(w/v) of sodium alginate and 17 wt% of glycerol and for maximum EB was at 4.89%(w/v) of sodium alginate and 49.65 wt% of glycerol. The optimum parameter of the films had revealed the better TS was at lower sodium alginate content and better EB was at higher glycerol content. In terms of thermal stability, the thermal decomposition temperature (Tonset) of sodium alginate decreased with the incorporation of glycerol.

Impact of Rheology-Based Optimum Parameters on Enhancing the Mechanical Properties and Fatigue of Additively Manufactured Acrylonitrile-Butadiene-Styrene/Graphene Nanoplatelet Composites.

This study investigates the interaction between static and fatigue strength and the rheological properties of acrylonitrile-butadiene-styrene (ABS) polymer reinforced with graphene nanoplatelets (GNPs) in both filament and 3D-printed forms. Specifically focusing on the effects of 1.0 wt.% GNPs, the study examines their influence on static/fatigue responses. The rheological behaviour of pure ABS polymer and ABS/GNPs nanocomposite samples, fabricated through material extrusion, is evaluated. The results indicated that the addition of 1.0 wt.% GNPs to the ABS matrix improved the elastic modulus of the nanocomposite filaments by up to about 34%, while reducing their ductility by approximately 60%. Observations revealed that the static and fatigue responses of the composite filament materials and 3D-printed parts were not solely attributed to differences in mechanical properties, but were also influenced by extrusion-related process parameters. The shark-skin effect, directly related to the material's rheological properties, had a major impact on static strength and fatigue life. The proposed method involved adjusting the temperature of the heating zones of the extruder during filament production to enhance the static response of the filament and using a higher nozzle temperature (270 °C) to improve the fatigue life of the 3D-printed samples. The findings reveal that the proposed parameter optimisation led to filaments with minimised shark-skin effects, resulting in an improvement in ultimate tensile strength compared to pure ABS. Moreover, the 3D-printed samples produced with a higher nozzle temperature exhibited increased fatigue lives compared to those manufactured under identical conditions as pure ABS.

Optimisation of Exhaust Emissions, Vibration, and Noise of Unmodified Diesel Engine Fuelled with Canola Biodiesel-Diesel Blends with Natural Gas Addition by Using Response Surface Methodology

The paper presents methods to determine the optimum input parameters of CNG addition, biodiesel blend ratio, and engine speed to improve engine responses in terms of exhaust emissions, vibration, and noise of CNG-biodiesel-diesel fuelled engine. Box-Behnken based on response surface methodology was used to predict and optimise input parameters. Variance analysis was applied to determine the significant relationship between the input parameters and engine responses. At optimum input parameters (CNG addition=9.24 L/min, biodiesel blend ratio=40%, engine speed=1524.24 rpm), the optimum engine responses of NOx, CO, CO2, O2, engine vibration acceleration, and noise were 93.77 ppm, 438.05 ppm, 1.47%, 18.59%, 37.17 m/s2 and 91.34 dB[A], respectively. In terms of coefficient determination of R2, the values were 99.11%, 99.22%, 99.41%, 99.70%, 98.65%, and 98.60% respectively. The correlation between the optimised result and the engine test result showed an acceptable error limit for NOx, CO, CO2, O2, engine vibration acceleration, and noise as 4.2%, 3.8%, 4.9%, 0.25%, 4.12%, and 0.17%, respectively.

Evaluation of physicochemical properties, antioxidant capacity, and volatile flavor compounds during the wine fermentation of Mei (Prunus mume) fruit

In this study, Prunus mume (Mei) wine was produced from the fruits of a new variety Mei 'Laizhou Mixing’. The optimum process parameters (OPPs) of Mei wine (MW) fermentation were determined through an orthogonal experiment. We explored the physicochemical properties, antioxidant capacity, and volatile flavor compounds (VFCs) of MW and their correlation characteristics. Under the OPPs (A2B2C3D3) condition, MW containing approximately 6%(v/v) alcohol was obtained within three days of fermentation. After seven days of low-temperature clarification, the antioxidant capacity of MW was significantly higher than that of Mei juice, and the VFCs type and concentration significantly increased. A total of eight esters and one phenolic compound were produced during fermentation. The changes in the VFCs of MW were related to physicochemical properties and antioxidant capacity. This study provides insight into the changes in MW quality before and after fermentation.

Performance analysis of a novel air source ammonia/water cascade heat pump for heating buildings in subarctic climate

Performance of available air-source heat pumps (ASHP) for buildings is extremely influenced by the outdoor air temperature (OAT). When OAT falls below –20°C, especially in subarctic climate, most commercially available ASHPs lose their defined functionality. To address this issue, a novel cascade heat pump (CHP) is proposed that utilizes two natural (with zero global warming index) refrigerants: ammonia, aka R717, as the low stage (LS) refrigerant, and water, aka R718, as the high stage (HS) working fluid. The proposed system is equipped with two rotary vane compressors for LS and HS. To desuperheat the compressor discharge temperatures and increase the HS heating capacity, liquid refrigerant is injected into the chamber of both LS and HS compressors. The wet compression is thermodynamically modeled and validated against experimental data available in the literature. Optimum design parameters such as the maximum allowable temperatures during compression and the minimum vapor quality after injection are obtained where the COP is maximized. Total exergy destruction, number/location of injectors and the injected amounts are also investigated. The proposed CHP can deliver 6.35 kW heating load at 50°C with a COP of 1.985 when OAT is –40°C. From a broader perspective, the proposed CHP not only proves its efficacy in extremely cold subarctic climates but also emerges as a pivotal player in addressing the global warming issue. This is accomplished through a dual approach to decarbonization—firstly, by electrifying heating processes and secondly, by substituting phased-out refrigerants with environmentally friendly natural alternatives.