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At least 685 records · Page 38

Local Power-Voltage Sensitivity and Thevenin Impedance Estimation from Phasor Measurements

This paper describes how to use voltage phasor measurements to produce a sensitivity matrix that describes how real and reactive power injections at a node on a distribution network affect the local voltage magnitude and angle. Rather than estimating the sensitivity directly, the voltage phasor measurements and power commands/measurements are used to estimate the unbalanced, three-phase Thevenin impedance. The Thevenin impedance estimation is conducted using recursive least squares on temporal difference measurements. The Thevenin impedance and voltage phasor measurement are then used to build the local power-voltage sensitivity matrix with the closed form expression for the Jacobian of the power flow manifold. Hardware-in-the-loop simulations with phasor measurement units providing real phasor measurements are used to evaluate the recursive temporal difference Thevenin impedance estimation and Thevenin-based power-voltage sensitivity methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Ultrahigh sensitivity of anomalous Hall effect sensor based on Cr-doped Bi 2 Te 3 topological insulator thin films

Anomalous Hall effect (AHE) was recently discovered in magnetic element-doped topological insulators (TIs), which promises low power consumption and high efficiency spintronics and electronics. This discovery broadens the family of Hall sensors. In this paper, AHE sensors based on Cr-doped Bi 2 Te 3 topological insulator thin films are studied with two thicknesses (15 and 65 nm). It is found, in both cases, that ultrahigh Hall sensitivity can be obtained in Cr-doped Bi 2 Te 3 . Hall sensitivity reaches 1666 Ω/T in the sensor with the 15 nm TI thin film, which is higher than that of the conventional semiconductor HE sensor. The AHE of 65 nm sensors is even stronger, which causes the sensitivity increasing to 2620 Ω/T. Furthermore, after comparing Cr-doped Bi 2 Te 3 with the previously studied Mn-doped Bi 2 Te 3 TI Hall sensor, the sensitivity of the present AHE sensor shows about 60 times higher in 65 nm sensors. Furthermore, the implementation of AHE sensors based on a magnetic-doped TI thin film indicates that the TIs are good candidates for ultrasensitive AHE sensors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Generalized Analytical Estimation of Sensitivity Matrices in Unbalanced Distribution Networks

Fast and accurate estimation of sensitivity matrices is significant for the enhancement of distribution system modeling and automation. Analytical estimations have mainly focused on voltage magnitude sensitivity to active/reactive power injections for unbalanced networks with Wye-connected loads and neglecting DERs' smart inverter functionality. Hence, this paper enhances the scope of analytical estimation of sensitivity matrices for unbalanced networks with 1- Φ, 2- Φ, and 3- Φ Delta/Wye-connected loads, DERs with smart inverter functionality, and substation/line step-voltage regulators (SVR). A composite bus model comprising of DER, Delta- and Wye-connected load is proposed to represent a generic distribution bus, which can be simplified to load, PV, or voltage-controlled bus as required. Furthermore, the proposed matrix-based analytical method consolidates voltage magnitude and angle sensitivity to active/reactive power injection and tap-position of all SVRs into a single algorithm. Extensive case studies on IEEE and EPRI networks show the accuracy and wide scope of the proposed algorithm compared to the existing benchmark method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SU-C-9A-07: Fabrication and Calibration of a Novel High-Sensitivity Collimator for Brain SPECT Imaging

Purpose: We have designed a novel collimator for brain SPECT imaging that yields greatly increased sensitivity near the center of the brain without loss of resolution. The collimator was manufactured and initial evaluation has been completed. Methods: The collimator was time-consuming and challenging to build. Because our desired hole pattern required substantial variations in hole angle, we designed two supporting plates to securely position about 34,000 hexagonal, slightly tapered, 75-mm long steel pins. The holes in the plates were modeled to yield the desired focal length, hole length and septal thickness. Molten lead was poured in between the plates, and all pins were removed after cooling. The sensitivity gain compared to a fan-beam collimator was measured using a point source placed along the central ray at several distances from the collimator face. Visual inspection of the holes was not possible as the collimator was sealed so it could be safely mounted on a SPECT system. Therefore, we prepared a 2D array of 768, ∼48μCi Tc-99m point sources, separated by 1.6 cm. The array was imaged for 10 minutes at 4 shifted locations to reduce sampling distance to 8 mm. Results: The sensitivity of the novel cone-beam collimator varied with distance from the detector face; it was higher than that of the fan-beam collimator by factors ranging from 3 to 176. Examination of the projections of the 4×768 point sources revealed that fewer than 2% of the holes were fully or partially blocked, which indicates that the intensive manual fabrication process was very successful. Conclusion: We have designed and manufactured a novel collimator for brain SPECT imaging. As expected, the sensitivity is much higher than that of a fan-beam collimator. Because of differences between the manufactured collimator and its design, reconstruction of the data will require a measured system function.

60 APPLIED LIFE SCIENCES↗

TU-C-BRE-08: IMRT QA: Selecting Meaningful Gamma Criteria Based On Error Detection Sensitivity

Purpose: To develop a strategy for defining meaningful tolerance limits and studying the sensitivity of IMRT QA gamma criteria by inducing known errors in QA plans. Methods: IMRT QA measurements (ArcCHECK, Sun Nuclear) were compared to QA plan calculations with induced errors. Many (>24) gamma comparisons between data and calculations were performed for each of several kinds of cases and classes of induced error types with varying magnitudes (e.g. MU errors ranging from -10% to +10%), resulting in over 3,000 comparisons. Gamma passing rates for each error class and case were graphed against error magnitude to create error curves in order to represent the range of missed errors in routine IMRT QA using various gamma criteria. Results: This study demonstrates that random, case-specific, and systematic errors can be detected by the error curve analysis. Depending on location of the peak of the error curve (e.g., not centered about zero), 3%/3mm threshold=10% criteria may miss MU errors of up to 10% and random MLC errors of up to 5 mm. Additionally, using larger dose thresholds for specific devices may increase error sensitivity (for the same X%/Ymm criteria) by up to a factor of two. This analysis will allow clinics to select more meaningful gamma criteria based on QA device, treatment techniques, and acceptable error tolerances. Conclusion: We propose a strategy for selecting gamma parameters based on the sensitivity of gamma criteria and individual QA devices to induced calculation errors in QA plans. Our data suggest large errors may be missed using conventional gamma criteria and that using stricter criteria with an increased dose threshold may reduce the range of missed errors. This approach allows quantification of gamma criteria sensitivity and is straightforward to apply to other combinations of devices and treatment techniques.

60 APPLIED LIFE SCIENCES↗

TU-AB-BRA-04: Quantitative Radiomics: Sensitivity of PET Textural Features to Image Acquisition and Reconstruction Parameters Implies the Need for Standards

Purpose: Despite increased use of heterogeneity metrics for PET imaging, standards for metrics such as textural features have yet to be developed. We evaluated the quantitative variability caused by image acquisition and reconstruction parameters on PET textural features. Methods: PET images of the NEMA IQ phantom were simulated with realistic image acquisition noise. 35 features based on intensity histograms (IH), co-occurrence matrices (COM), neighborhood-difference matrices (NDM), and zone-size matrices (ZSM) were evaluated within lesions (13, 17, 22, 28, 33 mm diameter). Variability in metrics across 50 independent images was evaluated as percent difference from mean for three phantom girths (850, 1030, 1200 mm) and two OSEM reconstructions (2 iterations, 28 subsets, 5 mm FWHM filtration vs 6 iterations, 28 subsets, 8.6 mm FWHM filtration). Also, patient sample size to detect a clinical effect of 30% with Bonferroni-corrected α=0.001 and 95% power was estimated. Results: As a class, NDM features demonstrated greatest sensitivity in means (5–50% difference for medium girth and reconstruction comparisons and 10–100% for large girth comparisons). Some IH features (standard deviation, energy, entropy) had variability below 10% for all sensitivity studies, while others (kurtosis, skewness) had variability above 30%. COM and ZSM features had complex sensitivities; correlation, energy, entropy (COM) and zone percentage, short-zone emphasis, zone-size non-uniformity (ZSM) had variability less than 5% while other metrics had differences up to 30%. Trends were similar for sample size estimation; for example, coarseness, contrast, and strength required 12, 38, and 52 patients to detect a 30% effect for the small girth case but 38, 88, and 128 patients in the large girth case. Conclusion: The sensitivity of PET textural features to image acquisition and reconstruction parameters is large and feature-dependent. Standards are needed to ensure that prospective trials which incorporate textural features are properly designed to detect clinical endpoints. Supported by NIH grants R01 CA169072, U01 CA148131, NCI Contract (SAIC-Frederick) 24XS036-004, and a research contract from GE Healthcare.

60 APPLIED LIFE SCIENCES↗

Sensitivity estimation in time-of-flight list-mode positron emission tomography

Purpose: An accurate quantification of the images in positron emission tomography (PET) requires knowing the actual sensitivity at each voxel, which represents the probability that a positron emitted in that voxel is finally detected as a coincidence of two gamma rays in a pair of detectors in the PET scanner. This sensitivity depends on the characteristics of the acquisition, as it is affected by the attenuation of the annihilation gamma rays in the body, and possible variations of the sensitivity of the scanner detectors. In this work, the authors propose a new approach to handle time-of-flight (TOF) list-mode PET data, which allows performing either or both, a self-attenuation correction, and self-normalization correction based on emission data only. Methods: The authors derive the theory using a fully Bayesian statistical model of complete data. The authors perform an initial evaluation of algorithms derived from that theory and proposed in this work using numerical 2D list-mode simulations with different TOF resolutions and total number of detected coincidences. Effects of randoms and scatter are not simulated. Results: The authors found that proposed algorithms successfully correct for unknown attenuation and scanner normalization for simulated 2D list-mode TOF-PET data. Conclusions: A new method is presented that can be used for corrections for attenuation and normalization (sensitivity) using TOF list-mode data.

60 APPLIED LIFE SCIENCES↗

TU-H-CAMPUS-TeP2-03: High Sensitivity and High Resolution Fiber Based Micro-Detector for Sub-Millimeter Preclinical Dosimetry

Purpose: Current precision of small animal and cell micro-irradiators has continuously increased during the past years. Currently, preclinical irradiators can deliver sub-millimeter fields with micrometric precision but there are no water equivalent dosimeters to determine small field profiles and dose in the orthovoltage range of energies with micrometric resolution and precision. We have developed a fiber based micro-dosimeter with the resolution and dosimetric accuracy required for radiobiological research. Methods: We constructed two prototypes of micro-dosimeters based on different compositions of fiber scintillators to study the spatial resolution and dosimetric precision of small animal and cell micro-irradiators. The first has green output and the second has blue output. The blue output dosimeter has the highest sensitivity because it matches the spectral sensitivity of silicon photomultipliers. A blue detector with 500um cross section was built and tested respect to a CC01 ion chamber, film, and the 1500um green output detector. Orthovoltage fields from 1×1mm2 to 5×5mm2 were used for detector characteristics comparison. Results: The blue fiber dosimeter shows great agreement with films and matches dose measurements with the gold-standard ion chamber for 5×5mm2 fields. The detector has the appropriate sensitivity to measure fields from 1×1mm2 to larger sizes with a 1% dosimetric accuracy. The spatial resolution is in the sub-millimeter range and the spectral matching with the photomultiplier allows reducing the sensor cross section even further than the presented prototype. These results suggest that scintillating fibers combined with silicon photomultipliers is the appropriate technology to pursue micro-dosimetry for small animals and disperse cell samples. Conclusion: The constructed detectors establish a new landmark for the resolution and sensitivity of fiber based microdetectors. The validation of the detector in our small animal and cell irradiator shows that they are appropriate for preclinical and micro single cell irradiation quality assurance and dosimetry.

60 APPLIED LIFE SCIENCES↗

Introduction of a novel ultrahigh sensitivity collimator for brain SPECT imaging

Purpose: Noise levels of brain SPECT images are highest in central regions, due to preferential attenuation of photons emitted from deep structures. To address this problem, the authors have designed a novel collimator for brain SPECT imaging that yields greatly increased sensitivity near the center of the brain without loss of resolution. This hybrid collimator consisted of ultrashort cone-beam holes in the central regions and slant-holes in the periphery (USCB). We evaluated this collimator for quantitative brain imaging tasks. Methods: Owing to the uniqueness of the USCB collimation, the hole pattern required substantial variations in collimator parameters. To utilize the lead-casting technique, the authors designed two supporting plates to position about 37 000 hexagonal, slightly tapered pins. The holes in the supporting plates were modeled to yield the desired focal length, hole length, and septal thickness. To determine the properties of the manufactured collimator and to compute the system matrix, the authors prepared an array of point sources that covered the entire detector area. Each point source contained 32 μCi of Tc-99m at the first scan time. The array was imaged for 5 min at each of the 64 shifted locations to yield a 2-mm sampling distance, and hole parameters were calculated. The sensitivity was also measured using a point source placed along the central ray at several distances from the collimator face. High-count projection data from a five-compartment brain phantom were acquired with the three collimators on a dual-head SPECT/CT system. The authors calculated Cramer-Rao bounds on the precision of estimates of striatal and background activity concentration. In order to assess the new collimation system to detect changes in striatal activity, the authors evaluated the precision of measuring a 5% decrease in right putamen activity. The authors also reconstructed images of projection data obtained by summing data from the individual phantom compartments. Results: The sensitivity of the novel cone-beam collimator varied with distance from the detector face; it was higher than that of the fan-beam collimator by factors ranging from 2.7 to 162. Examination of the projections of the point sources revealed that only a few holes were distorted or partially blocked, indicating that the intensive manual fabrication process was very successful. Better reconstructed phantom images were obtained from the USCB+FAN collimator pair than from either LEHR or FAN collimation. For the left caudate, located near the center of the brain, the detected counts were 9.8 (8.3) times higher for UCSB compared with LEHR (FAN), averaged over 60 views. The task-specific SNR for detecting a 5% decrease in putamen uptake was 7.4 for USCB and 3.2 for LEHR. Conclusions: The authors have designed and manufactured a novel collimator for brain SPECT imaging. The sensitivity is much higher than that of a fan-beam collimator. Because of differences between the manufactured collimator and its design, reconstruction of the data requires a measured system matrix. The authors have demonstrated the potential of USCB collimation for improved precision in estimating striatal uptake. The novel collimator may be useful for early detection of Parkinson’s disease, and for monitoring therapy response and disease progression.

60 APPLIED LIFE SCIENCES↗

Combining Emergent Constraints for Climate Sensitivity

A method is proposed for combining information from several emergent constraints into a probabilistic estimate for a climate sensitivity proxy Y such as equilibrium climate sensitivity (ECS). The method is based on fitting a multivariate Gaussian PDF for Y and the emergent constraints using an ensemble of global climate models (GCMs); it can be viewed as a form of multiple linear regression of Y on the constraints. The method accounts for uncertainties in sampling this multidimensional PDF with a small number of models, for observational uncertainties in the constraints, and for overconfidence about the correlation of the constraints with the climate sensitivity. Its general form (Method C) accounts for correlations between the constraints. Method C becomes less robust when some constraints are too strongly related to each other; this can be mitigated using regularization approaches such as ridge regression. An illuminating special case, Method U, neglects any correlations between constraints except through their mutual relationship to the climate proxy; it is more robust to small GCM sample size and is appealingly interpretable. These methods are applied to ECS and the climate feedback parameter using a previously published set of 11 possible emergent constraints derived from climate models in the Coupled Model Intercomparison Project (CMIP). The ±2σ posterior range of ECS for Method C with no overconfidence adjustment is 4.3 ± 0.7 K. For Method U with a large overconfidence adjustment, it is 4.0 ± 1.3 K. This study adds confidence to past findings that most constraints predict higher climate sensitivity than the CMIP mean.

54 ENVIRONMENTAL SCIENCES↗

Proposal and application of ROM-Lasso method for sensitivity coefficient evaluation

We propose a novel method for evaluating sensitivity coefficients of neutronics parameters to cross sections, so-called the reduced-order modeling technique ROM-Lasso. In this method, cross sections of interest are randomly sampled, and corresponding perturbed core analyses are performed. Then, the sensitivity coefficient vector of the higher-level model is expanded via the active subspace bases obtained with the lower-level model whose dimensional complexity is smaller than that of the higher-level model, and the expansion coefficients are estimated by the Lasso regression. A unique feature of the ROM-Lasso method allows the use of different bases optimized for each neutronics parameter. We conducted a verification calculation for an accelerator-driven system and demonstrated that the ROM-Lasso method can reproduce the sensitivity coefficients with a much smaller number of forward calculations than the direct method. The proposed method can be used to practically evaluate sensitivity coefficients. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sensitivity analyses of a homogeneous model and a RZ model of the MYRRHA reactor in its critical configuration

Two homogenized models of the MYRRHA (Multi-purpose hybrid Research Reactor for High-tech Applications) reactor in its critical configuration are presented in this study. Both models will be verified by comparing the main reactor parameters (K{sub eff}, β{sub eff} and Λ) with those of the heterogeneous model and a sensitivity analysis will be performed. A sensitivity analysis of some important parameters related to reactivity, namely the vacuum coefficient, the Doppler and the power peaking factors, is also presented. The study of the vacuum coefficient has been carried out by analyzing two possible scenarios: 50% vacuum in the coolant (lead bismuth eutectic) and 100%, obtaining a list of the 10 reactions and nuclides that most affect the k{sub eff} value. With respect to the Doppler coefficient, it will be seen that a 300 degree increase in fuel temperature (starting at 800 K) results in a reduction of the total reactivity of the system by 134 pcm.. Finally, the map of the power peaking factors will be shown, as well as a sensitivity analysis. For making the sensitivity calculations Serpent-2 reactor physics Monte Carlo code has been used and JEFF-3.3 library has been chosen in order to continue with the OECD/NEA WPEC SG46 work evaluating the nuclear data of this library. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Proof-of-Concept Study for Uncertainty Quantification and Sensitivity Analysis using the BRL Shaped-Charge Example

These are the slides for a graduate presentation at Mississippi State University. It covers the following: the BRL Shaped-Charge Geometry in PAGOSA, mesh refinement study, surrogate modeling using a radial basis function network (RBFN), ruling out parameters using sensitivity analysis (equation of state study), uncertainty quantification (UQ) methodology, and sensitivity analysis (SA) methodology. In summary, a mesh convergence study was used to ensure that solutions were numerically stable by comparing PDV data between simulations. A Design of Experiments (DOE) method was used to reduce the simulation space to study the effects of the Jones-Wilkins-Lee (JWL) Parameters for the Composition B main charge. Uncertainty was quantified by computing the 95% data range about the median of simulation output using a brute force Monte Carlo (MC) random sampling method. Parameter sensitivities were quantified using the Fourier Amplitude Sensitivity Test (FAST) spectral analysis method where it was determined that detonation velocity, initial density, C1, and B1 controlled jet tip velocity.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Sensitivity analysis of FeCrAl cladding and U3Si2 fuel under accident conditions

The purpose of this milestone report is to highlight the results of sensitivity analyses performed on two accident tol- erant fuel concepts: U3Si2 fuel and FeCrAl cladding. The BISON fuel performance code under development at Idaho National Laboratory was coupled to Sandia National Laboratories’ DAKOTA software to perform the sensitivity analyses. Both Loss of Coolant (LOCA) and Station blackout (SBO) scenarios were analyzed using main effects studies. The results indicate that for FeCrAl cladding the input parameters with greatest influence on the output metrics of interest (fuel centerline temperature and cladding hoop strain) during the LOCA were the isotropic swelling and fuel enrichment. For U3Si2 the important inputs were found to be the intergranular diffusion coefficient, specific heat, and fuel thermal conductivity. For the SBO scenario, Young’s modulus was found to be influential in FeCrAl in addition to the isotropic swelling and fuel enrichment. Contrarily to the LOCA case, the specific heat of U3Si2 was found to have no effect during the SBO. The intergranular diffusion coefficient and fuel thermal conductivity were still found to be of importance. The results of the sensitivity analyses have identified areas where further research is required including fission gas behavior in U3Si2 and irradiation swelling in FeCrAl. Moreover, the results highlight the need to perform the sensitivity analyses on full length fuel rods for SBO scenarios.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

(U) Second-Order Sensitivity Analysis of Uncollided Particle Contributions to Radiation Detector Responses Using Ray-Tracing

The Second-Level Adjoint Sensitivity System (2nd-LASS) that yields the second-order sensitivities of a response of uncollided particles with respect to isotope densities, cross sections, and source emission rates is derived in Refs. 1 and 2. In Ref. 2, we solved problems for the uncollided leakage from a homogeneous sphere and a multiregion cylinder using the PARTISN multigroup discrete-ordinates code. In this memo, we derive solutions of the 2nd-LASS for the particular case when the response is a flux or partial current density computed at a single point on the boundary, and the inner products are computed using ray-tracing. Both the PARTISN approach and the ray-tracing approach are implemented in a computer code, SENSPG. The next section of this report presents the equations of the 1st- and 2nd-LASS for uncollided particles and the first- and second-order sensitivities that use the solutions of the 1st- and 2nd-LASS. Section III presents solutions of the 1st- and 2nd-LASS equations for the case of ray-tracing from a detector point. Section IV presents specific solutions of the 2nd-LASS and derives the ray-trace form of the inner products needed for second-order sensitivities. Numerical results for the total leakage from a homogeneous sphere are presented in Sec. V and for the leakage from one side of a two-region slab in Sec. VI. Section VII is a summary and conclusions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Evaluation of Oxygen Consumption as a Sensitive Measure of Electrical Cable Polymer Insulation Degradation

Polymers used as dielectric materials in nuclear grade electrical cables, such as cross-linked polyethylene (XLPE) and ethylene-propylene rubber (EPR), are long-lived and durable. Estimating the decades-long useful service life of polymers experimentally in a feasible timeframe of weeks or months requires greatly accelerated aging in the laboratory at elevated temperatures and/or gamma dose rates. Many limitations of accelerated aging, such as due to artefacts of the process including diffusion limited oxidation and dose rate effects, have been identified that can make accurate lifetime prediction at service conditions challenging. This can be due to differences in degradation mechanisms between rapid and extended aging or to the presence of induction periods during which early aging is undetectable using common metrics of polymer insulation characterization such as tensile elongation at break. Conceptually, an ideal measure of aging would track clearly and predictably with material changes throughout the lifecycle of the evolving material state from early aging through end of useful life. With such a metric accelerated aging could be performed at much milder conditions, conditions closer to those found in long term service, and end of life calculated from the early data. Oxygen consumption has previously been proposed as a sensitive measure of insulation polymer oxidation that might meet such desirable characteristics. In this work, nuclear cable insulation samples of the two most common types, XLPE and EPR, from two of the most sourced manufacturers, RSCC and The Okonite Company, were subjected to gamma irradiation at dose rates of 100, 200, and 300 Gy/hr for up to 42 days at 26°C. The aged samples were used to evaluate oxygen consumption as a sensitive measure of aging for these materials and these conditions. For comparison and validation, the aged samples were also characterized using the more conventional tests of mass change, density, carbonyl index, and yellowness index. For both materials, oxygen consumption during irradiation was found to track consistently with applied dose—oxygen consumption rate was linear with time. Mass change and carbonyl index were also clearly proportional to exposure dose. Yellowness index, a surface sensitive measure, was observed to increase linearly with dose at low exposure levels before plateauing. Sample density was not observed to change under the conditions explored. Oxygen consumption was found to be a particularly sensitive metric to measure the degradation of polymeric cable insulation exposed to radiation. Oxygen consumption was compared to Arrhenius and time-temperature-superposition methods for activation energy calculation using literature date and found to be a useful and viable alternative for lifetime prediction. The techniques developed in this work are anticipated to be valuable in the estimation of insulation aging rates under mild conditions approaching service conditions. Direction comparison of useful life prediction by oxygen consumption with prediction via Arrhenius methodology for thermal aging and existing methods for radiation and combined thermal/radiation aging would serve to further validate this promising approach and refine our understanding of material-specific aging rates.

36 MATERIALS SCIENCE↗

Parametric and Sensitivity Analysis of a Steam Generator Model Using Python and Machine-Learning Tools

For this study, we used Python and machine-learning tools to perform a comprehensive parametric and sensitivity analysis on a steam generator (SG) model. (The Python model was based on a previously completed MATLAB framework for the Holtec SMR-160 SG.) We investigated the influence of various input parameters (e.g., heat transfer coefficient [HTC], Nusselt number, and heat exchanger effectiveness) on the system’s output. With machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN), which was developed at Idaho National Laboratory, we were then able to perform an automated analysis of the SG inputs’ effect on the HTC. The analysis results give valuable insights into the performance and optimization of SG systems. We found the inlet mass flow rate (MFR) to have the greatest impact on the HTC, followed closely by the inlet temperature, and then pressure. Shifting of the input parameters causes the location of the maximum HTC along the SG length to change incrementally. The cold leg (CL) MFR was also found to impact the HTC magnitude as well as the location of the maximum HTC. At between 0.4–0.9 of the total SG length, the input parameters experience maximum impact on the HTC, leading us to suggest that sensors be efficiently placed on the SG so as to closely and effectively monitor thermal-hydraulic properties during reactor operation. We also found that the sensitivity data calculated manually agrees with the RAVEN – based data, confirming the same range of maximum sensitivity. However, the RAVEN-based analysis showed that cold leg pressure and hot leg temperature have a greater impact on the heat transfer coefficient than the mass flow rate, implying that a manual sensitivity study taking only two samples is not accurate.

20 FOSSIL-FUELED POWER PLANTS↗

Aerodynamic Sensitivities over Separable Shape Tensors

Here, we present a comprehensive aerodynamic sensitivity analysis of airfoil parameterization informed by separable shape tensors. This parameterization approach uniquely benefits the design process by isolating various well-studied shape characteristics, such as airfoil thickness, and providing a well-regulated low-dimensional parameter domain for aerodynamic designs. Exploring the aerodynamic sensitivities of this novel parameterization can provide valuable insights for more robust designs and future manufacturing efforts. We construct a data-driven parameter space of airfoils using principal geodesic analysis of separable shape tensors informed by a curated database containing almost 20,000 suitable engineering airfoils. Analyzing the shape reconstruction error and the maximum mean discrepancy between joint distributions of aerodynamic quantities, we study the dimensionality of the learned parameter space. This simple numerical experiment demonstrates a dramatic dimension reduction that retains design effectiveness and promotes regularity of the shape representations. Finally, we generate new airfoils and use the HAM2D Reynolds-averaged Navier–Stokes solver to predict lift, drag, and moment coefficients. We compute multiple sensitivity metrics to quantify and assert the consistency of parameter influence on the aerodynamic quantities. We also explore low-dimensional polynomial ridge approximations to motivate physical intuitions and offer explanations of the approximated sensitivities.

17 WIND ENERGY↗