Impedance spectroscopy characterization of neutron irradiated thermoelectric modules for space nuclear power

The European Space Agency is currently supporting the research and development of advanced radioisotope power systems utilising thermoelectric modules. The performance of thermoelectric modules following exposure to neutron radiation is of significant interest due to the likely application of radioisotope thermoelectric generators in deep space exploration or planetary landers requiring prolonged periods of operation. This study utilises impedance spectroscopy to characterise the effects of neutron irradiation on the performance of complete thermoelectric modules, as opposed to standalone material. For a 50 We americium-241 radioisotope thermoelectric generator design, it is estimated that the TE modules could be exposed to a total integrated flux of approximately 5 × 1013 neutrons cm-2 (>1 MeV). In this study, an equivalent neutron dose was simulated experimentally via an acute 2-hour exposure in a research pool reactor. Bi2Te3-based thermoelectric modules with different leg aspect ratios and microstructures were investigated. Gamma-ray spectroscopy was initially used to identify activated radionuclides and hence quantify irradiation induced transmutation doping. To evaluate the thermoelectric properties pre- and post-irradiation, impedance spectroscopy characterization was employed. Isochronal thermal annealing of defects imparted by the irradiation process, revealed that polycrystalline based modules required significantly higher temperature than those with a monolithic microstructure. Whilst this may indicate a greater susceptibility to neutron irradiation, all tested modules demonstrated sufficient radiation hardness for use within an americium-241 radioisotope thermoelectric generator. Furthermore, the work reported demonstrates that impedance spectroscopy is a highly capably diagnostic tool for characterising the in-service degradation of complete thermoelectric devices

Mortality of emergency abdominal surgery in high-, middle- and low-income countries

Background: Surgical mortality data are collected routinely in high-income countries, yet virtually no low- or middle-income countries have outcome surveillance in place. The aim was prospectively to collect worldwide mortality data following emergency abdominal surgery, comparing findings across countries with a low, middle or high Human Development Index (HDI). Methods: This was a prospective, multicentre, cohort study. Self-selected hospitals performing emergency surgery submitted prespecified data for consecutive patients from at least one 2-week interval during July to December 2014. Postoperative mortality was analysed by hierarchical multivariable logistic regression. Results: Data were obtained for 10 745 patients from 357 centres in 58 countries; 6538 were from high-, 2889 from middle- and 1318 from low-HDI settings. The overall mortality rate was 1⋅6 per cent at 24 h (high 1⋅1 per cent, middle 1⋅9 per cent, low 3⋅4 per cent; P < 0⋅001), increasing to 5⋅4 per cent by 30 days (high 4⋅5 per cent, middle 6⋅0 per cent, low 8⋅6 per cent; P < 0⋅001). Of the 578 patients who died, 404 (69⋅9 per cent) did so between 24 h and 30 days following surgery (high 74⋅2 per cent, middle 68⋅8 per cent, low 60⋅5 per cent). After adjustment, 30-day mortality remained higher in middle-income (odds ratio (OR) 2⋅78, 95 per cent c.i. 1⋅84 to 4⋅20) and low-income (OR 2⋅97, 1⋅84 to 4⋅81) countries. Surgical safety checklist use was less frequent in low- and middle-income countries, but when used was associated with reduced mortality at 30 days. Conclusion: Mortality is three times higher in low- compared with high-HDI countries even when adjusted for prognostic factors. Patient safety factors may have an important role. Registration number: NCT02179112 (http://www.clinicaltrials.gov)

SVC Parameters Optimization Using a Novel Integrated MCDM Approach

Nowadays, multi-criteria decision-making (MCDM) methods are used widely in many fields of research and applications. Many studies have shown that MCDM approaches are effective in determining the optimal solution to a variety of symmetrical and asymmetrical problems with numerous parameters. This article investigates a novel approach using multi criteria decision making (MCDM) to optimize the parameters of static var compensator (SVC) and power system stabilizers (PSS). The proposed technique integrates similarity membership function reduction algorithm (SMFRA), removal effects of criteria (REC) and combined compromise solution (CoCoSo). In the first stage, (SMFRA) is employed to select the most dominant controller parameters in the optimization process. Secondly, the weights of the reduced parameters are computed based on (REC). Finally, (CoCoSo) method searches for the optimal setting parameters. A detailed sensitivity analysis is presented to evaluate the obtained results. It is found that the suggested integrated technique is time saving, easily implemented and of low computation burden, which can successfully be implemented to solve a wide range of issues, both comparable and dissimilar

Extraction of Solar Module Parameters using a Novel Optimization Technique

The parameters of a Photovoltaic (PV) model are pivotal in gauging its efficiency under varying sunlight irradiances, temperatures, and different load scenarios. Determining these PV model parameters poses a complex non-linear optimization challenge. This study is based on a new metaheuristic optimization algorithm called the Pelican Optimization Algorithm (POA) to discern the unknown parameters of the PV model. The suggested POA algorithm underwent testing using a monocrystalline panel, encompassing its single-diode configuration. The objective function is designed to minimize the root of the mean squared errors between the predicted and actual current values, adhering to specific parameter constraints. Various statistical error metrics were utilized to emphasize the performance of the proposed algorithm. A comparative analysis with other well-established algorithms was conducted, indicating that POA stands out as highly competitive since it showcases superior efficiency in parameter identification compared to its counterparts

Optimization of Observer Feedback Gains for Stable Sensorless IM Drives at Very Low Frequencies: A Comparative Study between GA and PSO

Instability of an adaptive flux observer (AFO) in the regenerating mode at low frequencies is a great challenge of sensorless induction motor (SIM) drives. Zero observer feedback gains (OFGs) in the regenerating mode at low frequencies are the main reasons for moving the dominant zero of the speed estimators to the unstable region. OFGs should be appropriately selected to transfer the unstable dominant zero to the stable region. In this paper, genetic algorithm (GA) and particle swarm optimization (PSO) techniques were used to design the OFGs for a stable observer. A fair comparison of the dominant zero location between the two approaches using the optimized OFGs is presented under parameter deviation. Analytical results and the design procedure of the OFGs using the two approaches are presented under deviations of stator resistance and mutual inductance to guarantee a stable dominant zero in the regenerating mode of IM. The dominant zeros obtained by PSO had a superior location to that obtained by GA for both stator resistance and mutual inductance deviations. It was observed that one of the gains had an almost constant value over a wide range of parameter deviations. However, the value of the other gain was dependent on the deviation of machine parameters. The advantage of using PSO over GA is that the relation between the gain and parameter deviation can be represented by a deterministic and mostly linear relationship. Simulation and experimental work of the SIM drive are presented and evaluated under the optimized OFGs

Optimization of Observer Feedback Gains for Stable Sensorless IM Drives at Very Low Frequencies: A Comparative Study between GA and PSO

Instability of an adaptive flux observer (AFO) in the regenerating mode at low frequencies is a great challenge of sensorless induction motor (SIM) drives. Zero observer feedback gains (OFGs) in the regenerating mode at low frequencies are the main reasons for moving the dominant zero of the speed estimators to the unstable region. OFGs should be appropriately selected to transfer the unstable dominant zero to the stable region. In this paper, genetic algorithm (GA) and particle swarm optimization (PSO) techniques were used to design the OFGs for a stable observer. A fair comparison of the dominant zero location between the two approaches using the optimized OFGs is presented under parameter deviation. Analytical results and the design procedure of the OFGs using the two approaches are presented under deviations of stator resistance and mutual inductance to guarantee a stable dominant zero in the regenerating mode of IM. The dominant zeros obtained by PSO had a superior location to that obtained by GA for both stator resistance and mutual inductance deviations. It was observed that one of the gains had an almost constant value over a wide range of parameter deviations. However, the value of the other gain was dependent on the deviation of machine parameters. The advantage of using PSO over GA is that the relation between the gain and parameter deviation can be represented by a deterministic and mostly linear relationship. Simulation and experimental work of the SIM drive are presented and evaluated under the optimized OFGs

The impact of dietary supplementation of polysaccharide derived from Polygonatum sibiricum on growth, antioxidant capacity, meat quality, digestive physiology, and gut microbiota in broiler chickens

ABSTRACT: Polygonatum sibiricum polysaccharide (PSP) has demonstrated diverse medicinal properties, extensively researched for human applications. Nonetheless, there is a lack of studies investigating the potential advantages of PSP in poultry farming. The present study investigated the impact of incorporating PSP into broiler diets on their growth performance, meat quality, blood metabolites, antioxidative status, and ileal histomorphology. Two hundred and forty-one-day-old male Ross-308 broiler chicks (44.98 ± 0.79 g) were randomly assigned to 3 experimental groups, with 8 replicates of 10 birds each. The birds were fed diets supplemented with PSP at 0, 400, and 800 mg/kg (control, PSP400, and PSP800, respectively). The results revealed a linear (P > 0.05) improvement in body weight gain, European production efficiency index, and feed conversion ratio during the grower (22–35 d) and overall periods (1–35 d). The pH levels in the ingluvies, ileum, and cecum exhibited a linear reduction (P > 0.05) in the PSP800 group at d 21 and d 35, respectively. Villus height and crypt depth were increased in the PSP400 and PSP800 groups compared to the control group. PSP400 and PSP800 groups exhibited decreased hydrogen peroxide (H2O2) levels and increased total antioxidant capacity (TAC) at 21 d, while at 35 d, TAC and sulfhydryl concentrations were elevated, and H2O2 was reduced only in the PSP800 group compared to the untreated one. No significant variations between the groups at the phylum and genus levels were observed, with Bacteroidetes and Firmicutes being the dominant phyla. However, PSP supplementation notably augmented Firmicutes and Verrucomicrobiota while reducing Euryarchaeota and Proteobacteria. At the genus level, there was an increase in Akkermansia, Alistipes, CHKCI001, Erysipelatoclostridium, and a decrease in Methanobrevibacter. Conclusively, incorporating PSP into broiler diets, particularly at a dosage of 800 mg/kg, improved growth performance, antioxidant capacity, and intestinal architecture and resulted in alterations in cecal microbiota without discernible impacts on digestive function and meat quality criteria