Analytic derivation of the correction factor for the improved coarse mesh method

The optimum design of a solid propulsion system consists of optimization of various disciplines including structure, aerothermodynamics, heat transfer, and grain geometry. In this paper, an efficient model of every discipline has been developed, and a suitable framework is introduced for these hard-coupled disciplines. Hybrid optimization algorithm is used to find the global optimum point including genetic algorithm and sequential quadratic programing. To show the performance of the proposed algorithm, the required correction factor values have been carefully derived using comparison between more than 10 real solid propulsion systems and the proposed algorithm results. According to the results, the derived correction factors are close to 1, with scattering level better than 0.97. In addition, it is shown that the proposed algorithm (errors < 8%) is more accurate in comparison with the conventional approach (errors < 17%). Then, for a case study, multidisciplinary analysis has been done based on 3 general objectives including dry mass, total mass, and specific impulse. It means that the optimum specific impulse is not the maximum value and the optimum dry mass is not the minimum value. Finally, the proposed algorithm can be used to directly derive the optimum configuration for every mission requirement.

The physical phenomenon of neutrons transport associated with eigenvalue problems appears in the criticality calculations of nuclear reactors and can be treated as a diffusion process. This paper presents a new method to solve eigenvalue problems of neutron diffusion in slab geometry and one energy group. This formulation combines the Finite Element Method, considered an intermediate mesh method, with the Spectral Green's Function Method, which is free of truncation errors, and it is considered a coarse mesh method. The novelty of this formulation is to approach the spatial moments of the neutron flux distribution by the first-order polynomials obtained from the spectral analysis of diffusion equation. The approximations provided by the new formulation allow obtaining accurate results in coarse mesh calculations. To validate the method, we compare the results obtained with the methods described in the literature, specifically the Diamond Difference method. The accuracy and the computational performance of the proposed formulation were characterized by solving benchmarks problems with a high degree of heterogeneity.

The correction factor (CF) is a crucial parameter in the back-calculation of drug consumption in wastewater-based epidemiology (WBE) studies. In this study, concentrations of 13 antidepressants and six metabolites were measured in wastewater samples for 11 consecutive months at the three largest treatment plants of Changshu, China. The monthly trends of mass loads and prescription volumes of the nine antidepressants widely detected in wastewater were largely parallel, indicating a strong correspondence between prescription and actual consumption during the study period. The correspondence yielded reliable CFs of target substances, among which the CF of norsertraline (14.5) was determined for the first time. The CFs based on excretion rates of venlafaxine and bupropion significantly overestimate consumption of the two drugs (by 76.5 and 82.4%, respectively), whereas the CF based on the excretion rate of N-desmethylcitalopram significantly underestimates its consumption (by 49.3%). The CFs of sertraline (16.4) and milnacipran (19.6) differ dramatically from those (500 and 1.8, respectively) based on excretion rates. The CFs used in previous studies would cause misleading pictures of regional mental health status and compromise the value of WBE. Therefore, the CFs derived here will play important roles in future studies as they yield a much more reliable estimation of consumption of major antidepressants.

The N Extra Element Theorem (NEET) is an alternative means of analysis for any transfer function of any linear system model, not restricted to electrical systems. Its principal distinction from conventional loop or node analysis is that a simpler reference system model in the absence of N designated "extra" elements is solved first, and the N extra elements are then restored via a correction factor. Parameters in the correction factor are various single injection and null double injection driving point immittances seen by the extra elements, and are all calculated upon the reference model. Thus, no calculation is performed upon a model containing any of the designated extra elements, and the final result is obtained by assembly of sequentially obtained results in a "divide and conquer" approach that is potentially easier, shorter, and which produces lower entropy forms than does the conventional approach. The NEET correction factor is a simultaneous bilinear representation of the extra elements, which can be immittances or dependent generators in any combination, and thus exposes explicitly the contribution of each extra element. An especially useful implementation of the NEET is to designate all the reactances as extra elements. The frequency response of the transfer function is then contained entirely in the NEET correction factor, which emerges directly as a ratio of polynomials in complex frequency s. The zeros as well as the poles can thus be obtained directly from the driving point resistances seen by the reactances, and it can also be determined whether any of the zeros or poles are exactly factorable. The approach throughout is to show how the NEET theorem can be useful in practical Design-Oriented Analysis, and emphasis is on the criteria by which the designer-analyst can take maximum advantage of the numerous choices of which elements to designate as "extra" and which of the many versions of the theorem to adopt.

Different detector properties will heavily affect the results of off-axis measurements outside of radiation fields, where a different energy spectrum is encountered. While a diode detector would show a high spatial resolution, it contains high atomic number elements, which lead to perturbations and energy-dependent response. An ionization chamber, on the other hand, has a much smaller energy dependence, but shows dose averaging over its larger active volume. We suggest a way to obtain spatial energy response corrections of a detector independent of its volume effect for profiles of arbitrary fields by using a combination of two detectors. Measurements were performed at an Elekta Versa HD accelerator equipped with an Agility MLC. Dose profiles of fields between 10×4cm² and 0.6×0.6cm² were recorded several times, first with different small-field detectors (unshielded diode 60012 and stereotactic field detector SFD, microDiamond, EDGE, and PinPoint 31006) and then with a larger volume ionization chamber Semiflex 31010 for different photon beam qualities of 6, 10, and 18MV. Correction factors for the small-field detectors were obtained from the readings of the respective detector and the ionization chamber using a convolution method. Selected profiles were also recorded on film to enable a comparison. After applying the correction factors to the profiles measured with different detectors, agreement between the detectors and with profiles measured on EBT3 film was improved considerably. Differences in the full width half maximum obtained with the detectors and the film typically decreased by a factor of two. Off-axis correction factors outside of a 10×1cm² field ranged from about 1.3 for the EDGE diode about 10mm from the field edge to 0.7 for the PinPoint 31006 25mm from the field edge. The microDiamond required corrections comparable in size to the Si-diodes and even exceeded the values in the tail region of the field. The SFD was found to require the smallest correction. The corrections typically became larger for higher energies and for smaller field sizes. With a combination of two detectors, experimentally derived correction factors can be obtained. Application of those factors leads to improved agreement between the measured profiles and those recorded on EBT3 film. The results also complement so far only Monte Carlo-simulated values for the off-axis response of different detectors.

Correction factors have been proposed for traumatic lumbar punctures (LPs) in febrile young infants. However, no studies have assessed their diagnostic utility. We sought to determine the proportion of traumatic LPs safely reclassified as low risk for bacterial meningitis using recently derived white blood cell (WBC) and protein correction factors. We retrospectively analyzed traumatic LPs among all febrile infants ≤60 days old at two tertiary paediatric hospitals from 2006 through 2018. Traumatic LPs were defined as ≥10,000 RBCs/mm3. Abnormal cerebrospinal fluid (CSF) WBCs and protein were adjusted downward using a newly derived correction factor (877 red blood cells [RBCs]: 1 WBC), three commonly used correction factors (500 WBCs: 1 RBC; 1,000 WBCs: 1 WBC; peripheral RBCs: WBCs), and a newly derived protein correction factor (1,000 RBCs: 0.011 g/L protein). There were 437 traumatic LPs including 357 (82%) with pleocytosis and 4 (0.9%) with bacterial meningitis. Overall, fewer infants were classified as having CSF pleocytosis using 877:1 and 1,000:1 ratios (38% and 43%, respectively), with 100% sensitivity and negative predictive value, and improved specificity (63% for 877:1, 58% for 1,000:1 ratios versus 19% for uncorrected counts). Among infants with pleocytosis, 877:1 and 1,000:1 ratios reclassified 191 (54%) and 171 (48%) as normal with no misclassified bacterial meningitis cases. Ratios of 500:1 and peripheral RBC:WBC misclassified 1 infant that had bacterial meningitis. Corrected CSF protein outperformed uncorrected protein in specificity but did not add diagnostic value following WBC-based correction. Correction ratios of 877:1 and 1,000:1 safely reclassified half of all febrile infants ≤60 days. These corrections should be considered when interpreting CSF results of traumatic LPs.

Thermodynamic determination of RNA duplex stability in magnesium solutions

The accurate measurement of field output factors at small field sizes typically encountered in SRS and IMRT is challenging. In this study we measured detector output ratios for small fields using a range of detectors and orientations, we then calculated correction factors for each detector using film dosimetry as reference to obtain field output factors. The calculated correction factors were compared to the ones from TRS 483. Detectors used were: EBT3 Gafchromic film, PTW semiflex 31010 chamber, PTW pinpoint 31016 chamber, PTW diamond (used in two different orientations) and PTW SRS 60018 diode. Photon beam energies were 6 MV flat and 7 MV FFF with square field sizes from 0.5 to 10.0 cm side. Semiflex and pinpoint chambers agreed well with film down to 2.0 cm field size but under-responded by up to 40% at 0.5 cm field size. At 0.5 cm field size, diamond with stem parallel to beam axis under-estimated field output factors by up to 6.2%; diamond with stem perpendicular to beam axis over-estimated field output factors by up to 1.5% and diode over-estimated field output factors by up to 6.5%. Calculated correction factors, in general, agreed with and confirmed those given in TRS 483 film is an acceptable alternative to Monte Carlo simulation for deriving correction factors for solid state detectors. For field sizes smaller than 1.0 cm, diamond detector with stem perpendicular to beam axis was the most adequate for field output factor measurement, although not recommended in TRS 483.

Recently, photoplethysmography (PPG)-based techniques have been extensively used for cuff-less, automated estimation of blood pressure because of their inexpensive and effortless acquisition technology compared to other conventional approaches. However, most of the reported PPG-based, generalized BP estimation methods often lack the desired accuracy due to pathophysiological diversity. Moreover, some methods rely on several correction factors, which are not globalized yet and require further investigation. In this paper, a simple and automated systolic (SBP) and diastolic (DBP) blood pressure estimation method is proposed based on patient-specific neural network (NN) modeling. Initially, 15 time-plane PPG features are extracted and after feature selection, only four selected features are used in the NN model for beat-to-beat estimation of SBP and DBP, respectively. The proposed technique also presents reasonable accuracy while used for generalized estimation of BP. Performance of the algorithm is evaluated on 670 records of 50 intensive care unit (ICU) patients taken from MIMIC, MIMIC II and MIMIC Challenge databases. The proposed algorithm exhibits high average accuracy with (mean[Formula: see text][Formula: see text][Formula: see text]SD) of the estimated SBP as ([Formula: see text]) mmHg and DBP as ([Formula: see text]) mmHg. Compared to the other generalized models, the use of patient-specific approach eliminates the necessity of individual correction factors, thus increasing the robustness, accuracy and potential of the method to be implemented in personal healthcare applications.

Many European countries assess the heating and cooling needs of buildings using the quasi-steady state calculation method described in EN ISO 13790. The energy need is calculated by establishing the monthly balance of heat losses and heat gains, and the dynamic effects are taken into consideration by introducing correlation factors. The difficulty of evaluating night-time ventilation with such a method comes from the strong influence of the dynamic effects. In this paper, two different calculation methods for modelling night-time ventilation have been developed and tested: one is based on correcting the convective heat transfer by ventilation using the factor 𝐶𝑣𝑒 (method proposed in the standard), and the other one introduces an adjustment factor 𝐶 on the relative heat gains. 288 simulations of a typical Danish office building have been performed using different boundary conditions: level of thermal mass, level of insulation, orientation, internal heat loads, duration and air change rate of night-time ventilation. For both methods, the derived correction factors are highly dependent on the thermal mass of the building. An influence of the period of activation of night-time ventilation has also been observed. Correlations have been developed and an improvement of the accuracy has been observed: the uncertainty on the annual energy consumption obtained with adjustment factor has been decreased from around 10 % down to 5%.

Quantification of SPECT myocardial perfusion images: Methodology and validation of the Yale-CQ method

We present a novel method for estimating the intrinsic fluorescence lifetime of deeply embedded localized fluorophores. It is based on scaling relations, characteristic for turbid media. The approach is experimentally substantiated by successfully reconstructing lifetimes for targets at depths up to 14.5 mm. A derived correction factor was determined from the product of the transport-corrected scattering coefficient mu(s) (') and the index of refraction n(r). In addition, data from an array of detectors (> or =2) can be used to estimate mu(s) (')n(r). The suggested algorithm is a promising tool for diagnostic fluorescence, since lifetime can be a sensitive indicator of the fluorophore environment.

Characterization of flow processes in multi-scale porous system (nanopores to mesopores) in tight rocks, such as the shales, is challenging because of the coexistence of various flow regimes in the porous media. Although some methods based on dusty gas model (DGM) have been applied to determine the apparent gas permeability of shales (Javadpour 2009, Freeman et al. 2011, Sakhaee-Pour and Bryant 2012, Chen et al. 2015), they fail to describe gas flow process in nanopores in detail. In this paper, we present an innovative methodology for estimating apparent gas permeability of shales by coupling multiscale flow mechanisms. The Lattice Boltzmann Method (LBM) with effective viscosity and a general second-order boundary condition is used to analyze the various flow regimes involved in the single microchannel. The desirable agreement between the simulation results and that from the DSMC studies for the rarefied flow prompts the application of the derived correction factor for estimating permeability of shale gas reservoirs. In order to realize this, the porous medium is represented by a bundle of capillaries with diameters determined by mercury injection capillary pressure (MICP) curves. The porous flow is simulated by Darcy's law with derived correction factor; the surface diffusion of adsorption gas in kerogen pores is simulated based on Langmuir model and Fick's law. An extensive integration based on fractal dimension is performed to estimate the total flow rate and thereby the apparent permeability of typical shale samples. MICP and a transient pressure pulse technique are employed on 7 shale samples to obtain the pore size distribution and permeability. The result shows that the estimated gas permeability matches well with the measured permeability with a 20% variation, indicating that the physics based model presented in this paper is highly effective in predicting gas permeability of tight formations, such as the shales.

Firefly, Teaching Learning Based Optimization and Kalman Filter Methods for GPS Receiver Position Estimation

A key component of research in the aerospace industry constitutes hypersonic flights (M>5) which includes the design of commercial high-speed aircrafts and development of rockets. Computational analysis becomes more important due to the difficulty in performing experiments and reliability of its results at these harsh operating conditions. There is an increasing demand from the industry for the accurate prediction of wall-shear and heat transfer with a low computational cost. Direct Numerical Simulations (DNS) create the standard for accuracy, but its practical usage is difficult and limited because of its high cost of computation. The usage of Reynold's Averaged Navier Stokes (RANS) simulations provide an affordable gateway for industry to capitalize its lower computational time for practical applications. However, the presence of existing RANS turbulence closure models and associated wall functions result in poor prediction of wall fluxes and inaccurate solutions in comparison with high fidelity DNS data. In recent years, machine learning emerged as a new approach for physical modeling. This thesis explores the potential of employing Machine Learning (ML) to improve the predictions of wall fluxes for hypersonic turbulent boundary layers. Fine-grid RANS simulations are used as training data to construct a suitable machine learning model to improve the solutions and predictions of wall quantities for coarser meshes. This strategy eliminates the usage of wall models and extends the range of applicability of grid sizes without a significant drop in accuracy of solutions. Random forest methodology coupled with a bagged aggregation algorithm helps in modeling a correction factor for the velocity gradient at the first grid points. The training data set for the ML model extracted from fine-grid RANS, includes neighbor cell information to address the memory effect of turbulence, and an optimal set of parameters to model the gradient correction factor. The successful demonstration of accurate predictions of wall-shear for coarse grids using this methodology, provides the confidence to build machine learning models to use DNS or high-fidelity modeling results as training data for reduced-order turbulence model development. This paves the way to integrate machine learning with RANS to produce accurate solutions with significantly lesser computational costs for hypersonic boundary layer problems.