Parametric estimation in photovoltaic modules using the crow search algorithm

<p>The problem of parametric estimation in photovoltaic (PV) modules considering manufacturer information is addressed in this research from the perspective of combinatorial optimization. With the data sheet provided by the PV manufacturer, a non-linear non-convex optimization problem is formulated that contains information regarding maximum power, open-circuit, and short-circuit points. To estimate the three parameters of the PV model (i.e., the ideality diode factor (a) and the parallel and series resistances (R_p and R_s)), the crow search algorithm (CSA) is employed, which is a metaheuristic optimization technique inspired by the behavior of the crows searching food deposits. The CSA allows the exploration and exploitation of the solution space through a simple evolution rule derived from the classical PSO method. Numerical simulations reveal the effectiveness and robustness of the CSA to estimate these parameters with objective function values lower than 1 × 10⁻²⁸ and processing times less than 2 s. All the numerical simulations were developed in MATLAB 2020a and compared with the sine-cosine and vortex search algorithms recently reported in the literature.</p>

Parametric estimation of gyrotactic microorganism hybrid nanofluid flow between the conical gap of spinning disk-cone apparatus

The silver, magnesium oxide and gyrotactic microorganism-based hybrid nanofluid flow inside the conical space between disc and cone is addressed in the perspective of thermal energy stabilization. Different cases have been discussed between the spinning of cone and disc in the same or counter wise directions. The hybrid nanofluid has been synthesized in the presence of silver Ag and magnesium oxide MgO nanoparticulate. The viscous dissipation and the magnetic field factors are introduced to the modeled equations. The parametric continuation method (PCM) is utilized to numerically handle the modeled problem. Magnesium oxide is chemically made up of Mg2+ and O2- ions that are bound by a strong ionic connection and can be made by pyrolyzing Mg(OH)2 (magnesium hydroxide) and MgCO3 (magnesium carbonate) at high temperature (700–1500 °C). For metallurgical, biomedical and electrical implementations, it is more efficient. Similarly, silver nanoparticle's antibacterial properties could be employed to control bacterial growth. It has been observed that a circulating disc with a stationary cone can achieve the optimum cooling of the cone-disk apparatus while the outer edge temperature remains fixed. The thermal energy profile remarkably upgraded with the magnetic effect, the addition of nanoparticulate in base fluid and Eckert number.

Real-­time parametric estimation of periodic wake-­foil interactions using bioinspired pressure sensing and machine learning

Periodic wake-­foil interactions occur in the collective swimming of bio­inspired robots. Wake interaction pattern estimation (and control) is crucial to thrust enhancement and propulsive efficiency optimization. In this paper, we study the wake interaction pattern estimation of two flapping foils in tandem configurations. The experiments are conducted at a Reynolds number of 1.41×10^4 in a water channel. A modified wake-­foil phase parameter Φ, which unifies the influences of inter­foil distance Lx, motion phase difference ∆φ and wake convection velocity Uv, is introduced to describe the wake interaction patterns parametrically. We use a differential pressure sensor on the downstream foil to capture wake interaction characteristics. Data sets at different tandem configurations are collected. The wake-­foil phase Φ is used to label the pressure signals. A one ­dimensional convolutional neural networks (1D-CNN) model is used to learn an end­to­end mapping between the raw pressure measurements and the wake-­foil phase Φ. The trained 1D-­CNN model shows accurate estimations (average error 3.5%) on random wake interaction patterns and is fast enough (within 40 ms). Then the trained 1D ­CNN model is applied to online thrust enhancement control of a downstream foil swimming in a periodic wake. Synchronous force monitoring and flow visualization demonstrate the effectiveness of the 1D-­CNN model. The limitations of the model are discussed. The proposed approach can be applied to the online estimation and control of wake interactions in the collective swimming and flying of biomimetic robots.

Parametric estimation of supplier's plant construction costs

Cost engineers of buying enterprises perform detailed product cost calculations of externally manufactured components. The aim of these calculations is to determine what a product should cost and to support purchasing functions in fact-based negotiations. While product cost engineers have deep knowledge in the calculation of direct cost, they need support in the calculation of supplier´s indirect cost categories. The calculation of industrial rent, which is expressed in annual cost per m² of occupied plant building floor space can be improved by providing accurate construction cost estimates. Construction costs are strongly impacting the calculation of supplier´s annual building depreciation, which is a crucial cost driver for the determination of the industrial rent. Academic literature is actually not providing an accurate and suitable cost model for product cost engineers, which is estimating construction cost per m² depending on different industrial building categories and alternative supplier plant locations. The paper aims to close this gap by applying linear regression analysis on a set of European construction cost data considering two industrial building categories: “warehouses/basic factory units” and “high-tech factories”. By regressing construction cost against construction labor rates within different supplier plant locations it was possible to form suitable and accurate parametric regression functions with R² values between 0.74 and 0.88. Next to high R² values acceptable mean average percentage errors between 7.45% and 11.77% could be realized by comparing estimated with observed construction cost. The estimation of industrial construction costs based on the paper´s results can be used to improve the calculation of industrial rent, which is one cost element, that has to be covered within product cost engineer´s Should Cost Calculations.

Non-parametric estimation of reference adjusted, standardised probabilities of all-cause death and death due to cancer for population group comparisons

Background Ensuring fair comparisons of cancer survival statistics across population groups requires careful consideration of differential competing mortality due to other causes, and adjusting for imbalances over groups in other prognostic covariates (e.g. age). This has typically been achieved using comparisons of age-standardised net survival, with age standardisation addressing covariate imbalance, and the net estimates removing differences in competing mortality from other causes. However, these estimates lack ease of interpretability. In this paper, we motivate an alternative non-parametric approach that uses a common rate of other cause mortality across groups to give reference-adjusted estimates of the all-cause and cause-specific crude probability of death in contrast to solely reporting net survival estimates. Methods We develop the methodology for a non-parametric equivalent of standardised and reference adjusted crude probabilities of death, building on the estimation of non-parametric crude probabilities of death. We illustrate the approach using regional comparisons of survival following a diagnosis of rectal cancer for men in England. We standardise to the covariate distribution and other cause mortality of England as a whole to offer comparability, but with close approximation to the observed all-cause region-specific mortality. Results The approach gives comparable estimates to observed crude probabilities of death, but allows direct comparison across population groups with different covariate profiles and competing mortality patterns. In our illustrative example, we show that regional variations in survival following a diagnosis of rectal cancer persist even after accounting for the variation in deprivation, age at diagnosis and other cause mortality. Conclusions The methodological approach of using standardised and reference adjusted metrics offers an appealing approach for future cancer survival comparison studies and routinely published cancer statistics. Our non-parametric estimation approach through the use of weighting offers the ability to estimate comparable survival estimates without the need for statistical modelling.

Application of the Crow Search Algorithm to the Problem of the Parametric Estimation in Transformers Considering Voltage and Current Measures

The problem of the electrical characterization of single-phase transformers is addressed in this research through the application of the crow search algorithm (CSA). A nonlinear programming model to determine the series and parallel impedances of the transformer is formulated using the mean square error (MSE) between the voltages and currents measured and calculated as the objective function. The CSA is selected as a solution technique since it is efficient in dealing with complex nonlinear programming models using penalty factors to explore and exploit the solution space with minimum computational effort. Numerical results in three single-phase transformers with nominal sizes of 20 kVA, 45 kVA, 112.5 kVA, and 167 kVA demonstrate the efficiency of the proposed approach to define the transformer parameters when compared with the large-scale nonlinear solver fmincon in the MATLAB programming environment. Regarding the final objective function value, the CSA reaches objective functions lower than 2.75×10−11 for all the simulation cases, which confirms their effectiveness in minimizing the MSE between real (measured) and expected (calculated) voltage and current variables in the transformer.

Estimation of Present-Day Strength of Concrete for a 40-year-old Building from Non-destructive Tests: A Case Study "

Assessment of the present health of existing concrete structures is necessary, particularly for enhancing the life of the infrastructure facilities reaching the end of their design life. The codes stipulate establishment of site-specific correlation expressions to estimate the compressive strength of concrete from indirect non-destructive tests (NDT) such as rebound hammer or ultrasonic pulse velocity tests. However, in certain circumstances, requisite number of partially destructive (core) tests required for establishing the site-specific equations might not be feasible. In such scenario, selection of a suitable correlation expression from literature has to be performed in a rational way, as discussed in this article with a case study of a 40-year-old concrete building. From the study, it has been ob-served that for the limited number of direct tests, the Indian code stipulation resulted in higher characteristic strength of concrete as compared to the parametric estimation, which can be attributed to the assumption of Normal distribution and code stipulated (conservative) standard deviation value. In case of the indirect estimation cases, the parametric characteristic strength was pretty close to the corresponding non-parametric values indicat-ing that the fitted distributions represented the strength values very well. Recommendations for the suitable cor-relation expression from literature applicable for estimation of equivalent strength from NDT for the structure, recommendation for characteristic compressive strength of concrete and the suggestions for accounting for the inaccuracies in estimated strength in subsequent structural re-analysis have been provided from the results of the study.