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At least 19 records

Multi-area parameter error identification for large power systems

Power grid model parameters may contain errors due to various reasons. Detecting and correcting parameter errors typically requires significant computational effort due to the size and complexity of the parameter database. While the normalized Lagrange multiplier (NLM) method can effectively detect, identify and correct parameter errors, its computational burden could rapidly grow with increasing system size. This paper addresses this issue by proposing a multi-area parameter error identification method. Each area has its own outlier detection tool for detecting the incorrect parameters and measurements within the area. On the other hand, due to the reduced redundancy at area boundaries, parameter errors on branches incident to boundary buses may not be detected. Such errors are subsequently detected by a coordination level estimator completing the system-wide parameter detection procedure. In conclusion, performance of the developed method is demonstrated using the IEEE 118-bus and 2000-bus Texas synthetic systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Uncertainty-Aware and Explainable Human Error Detection in the Operation of Nuclear Power Plants

The timely and accurate identification of incidents, such as human factor error, is important to restore nuclear power plants (NPPs) to a stable state. However, the identification of abnormal operating conditions is difficult because of the existence of multiple scenarios. In addition, to implement mitigation actions rapidly after an incident occurs, operators must accurately identify an incident by monitoring the trends of many variables. The mental burden posed by this can increase human error and cause failure in identifying incidents. Failure to identify incidents directly results in erroneous mitigation measures, which are detrimental to NPPs. In this study, we leverage uncertainty-aware models to identify such errors and thereby increase the chances of mitigating them. We use the data collected from a physical test bed. The goal is to identify both certain and accurate models. For this, the two main aspects of focus in this study are explainable artificial intelligence (XAI) and uncertainty quantification (UQ). While XAI elucidates the decision pathway, UQ evaluates decision reliability. Their integration paints a comprehensive picture, signifying that understanding decisions and their confidence should be interlinked. Thus, in this study we leverage UQ measures (e.g. entropy and mutual information) along with Shapley additive explanations to gain insights into the features contributing to both accuracy and uncertainty in error identification. Furthermore, our results show that uncertainty-aware models combined with XAI tools can explain the artificial intelligence–prescribed decisions, with the potential of better explaining errors for the operators.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Errors introduced in fission neutron spectrum measurements using a single reference

Measurements of physical quantities are often made relative to a reference quantity, simplifying the interpretation of the measurement and its uncertainties. However, if applied without careful considerations, this technique can carry with it a significant and complex systematic error that is usually ignored. For example, measurements of continuous neutron spectra relative to a reference spectrum yield a result that does not properly include the important effects of neutron scattering in the experimental environment. These effects act to distort the measured spectrum shape and create notable errors in spectrum-integrated quantities. While this effect is one of a series of known potential sources of systematic error including, but not limited to target impurities, angular distributions, incident beam flux, and others, the error introduced from differences in environmental scattering effects between the reference and desired spectra are frequently overlooked. In this work, we demonstrate the origin of this error using simulated data corresponding to measurements of the neutron-induced prompt fission neutron spectra of 233 U, 235 U, 238 U, and 239 Pu as well as the spontaneous fission neutron spectrum of 252 Cf. Errors in the spectrum shape can be as high as 10%–15% depending on the combination of incident and outgoing neutron energy. The spectrum integral and average spectrum energy also contain errors that change with incident neutron energy and can be as high as ~2%. Although this study is based on simulated data, we also show a method for proving that this error exists in an experimental data set and we show a correction that can be applied to results of this type to obtain a more accurate result, thereby largely removing systematic errors from environmental scattering effects. The potential for these kinds of errors should be considered in measurements producing continuous neutron spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Physically based correction of systematic errors of Rotating Shadowband Irradiometers

Accurate measurements of direct normal, diffuse horizontal and global horizontal irradiance (DNI, DHI and GHI) are needed for meteorological studies and are essential for the solar resource assessment at potential solar power plant sites. Often, these potential sites are remote and hence require robust sensors that require minimal maintenance that are not affected strongly by soiling. Therefore, Rotating Shadowband Irradiometers (RSI) are widely used for resource assessment. To achieve the required accuracy, corrections for the raw values of RSIs depending on systematic temperature, incidence angle and spectral errors must be used, and a thorough calibration of the sensor head must be applied. The existing correction functions are derived from comparisons of RSIs to thermopile radiometers at selected sites and therefore empirical. Their accuracy is considered to be site dependent. In this work a new correction and calibration method is presented that removes the systematic errors using a physical approach. It is based on information of the sensor properties as well as measurements of its directional response, and incorporates the atmospheric conditions at the measurement site. In this case, no empiric relations obtained from a specific site are required. The method requires estimates of the current DHI and GHI spectra during each measurement of the RSI. Based on these spectra, a spectral correction, which includes a spectrum dependent temperature correction, can be made without employing empirical relationships. The new physical calibration and correction method is tested at three sites and reaches similar results compared to the empirical functions. This is already achieved with rudimentary estimations of the GHI and DHI spectra and we expect that these estimations can be improved in the future. The results indicate that the physical approach reduces the problematic location dependence of the current calibration and correction methods. The physical correction and calibration method show promise for a further improvement of the RSI accuracy.

47 OTHER INSTRUMENTATION↗

Advances in statistical methods for cancer surveillance research: an age-period-cohort perspective

Background: Analysis of Lexis diagrams (population-based cancer incidence and mortality rates indexed by age group and calendar period) requires specialized statistical methods. However, existing methods have limitations that can now be overcome using new approaches. Methods: We assembled a “toolbox” of novel methods to identify trends and patterns by age group, calendar period, and birth cohort. We evaluated operating characteristics across 152 cancer incidence Lexis diagrams compiled from United States (US) Surveillance, Epidemiology and End Results Program data for 21 leading cancers in men and women in four race and ethnicity groups (the “cancer incidence panel”). Results: Nonparametric singular values adaptive kernel filtration (SIFT) decreased the estimated root mean squared error by 90% across the cancer incidence panel. A novel method for semi-parametric age-period-cohort analysis (SAGE) provided optimally smoothed estimates of age-period-cohort (APC) estimable functions and stabilized estimates of lack-of-fit (LOF). SAGE identified statistically significant birth cohort effects across the entire cancer panel; LOF had little impact. As illustrated for colon cancer, newly developed methods for comparative age-period-cohort analysis can elucidate cancer heterogeneity that would otherwise be difficult or impossible to discern using standard methods. Conclusions: Cancer surveillance researchers can now identify fine-scale temporal signals with unprecedented accuracy and elucidate cancer heterogeneity with unprecedented specificity. Birth cohort effects are ubiquitous modulators of cancer incidence in the US. The novel methods described here can advance cancer surveillance research.

60 APPLIED LIFE SCIENCES↗

The Challenges of Safe Troubleshooting Work

Troubleshooting work presents electrical and other workers with a challenging combination of physical hazards, working conditions, and time pressure, which can lead to unwanted outcomes if not carefully managed. Summaries of several incidents in which workers were injured or at risk of injury while performing troubleshooting work are presented, identifying organizational weaknesses and error precursors that contributed to each incident. The primary challenges include: Deranged equipment. Equipment that needs troubleshooting is not in a normal operating condition. Actions that are safe when the equipment is in a normal state may not be safe in the deranged state. Work planning and control. The steps taken in troubleshooting are most often determined by the results of the immediately previous diagnostic test, making effective work planning challenging. Multiple types of hazards. Most equipment will present a troubleshooting worker with several types of hazards, including hazardous energy as defined in 29 CFR 1910.147. Portions of the troubleshooting activity may be infeasible without these hazards present. Time pressure. Restoring operation of failed equipment often involves an explicit or implicit sense of urgency. There are effective methods for addressing each challenge, most of which require a combination of advance preparation and management commitment.

Mertz, David E.↗

Errors in reconstruction of dichroic X-ray orientation tomography due to polarization rotation of the incident beam

Dichroic X-ray tomography is a technique in which the crystal orientation or magnetization of a sample is resolved in three dimensions. The best-known uses of this technique are for observation of magnetic moments via circular dichroism, using left- and right-handed circularly polarized X-ray beams. Another variant uses linear dichroism to resolve the crystal orientation. In both these techniques, it is assumed that the absorption of X-rays along a path inside a material can be computed as a line integral of a local absorption coefficient along the ray path. For linear dichroism, this assumption is inaccurate because the polarization of the beam changes along the propagation direction when the optic axis of the material is not aligned along the polarization. In this work, a finite-element Maxwell solver is used to simulate tomography and reconstructions. The propagation effect can lead to significant errors in the reconstructed orientations. These errors may be mitigated by taking data at additional angles or by operating at energies at which the dichroism is weak. An iterative approach is proposed which may allow accurate reconstruction with fewer data than would otherwise be required.

X-ray linear dichroism↗

An improved method for direct incident solar radiation calculation from hourly solar insolation data in building energy simulation

Solar radiation considerably influences the energy consumption of buildings and the power production of building integrated photovoltaic (BIPV) systems. Hourly solar insolation (Wh/m 2 ), represented as the amount of solar irradiance collected on the ground during a 1-h period, is the most common solar radiation data available and widely used in weather files applied in building energy modeling programs (BEMPs). Because the solar beam and position vary over time, the use of hourly insolation data as the input might result in errors in the estimation of the direct incident solar radiation on a particular surface. In this study, methods used in BEMPs for direct incident solar radiation calculations are first analyzed, and an improved method adopting a new algorithm for estimating the solar irradiance is proposed. Furthermore, the algorithm assumes that the solar irradiance changes linearly within a 1-h period and can be estimated based on the solar irradiance at the half clock and slope. The collected direct normal solar irradiance data of 2016 from eight solar radiation stations in China were used to demonstrate the proposed method and evaluate its performance by comparing the results with those from three conventional methods used in BEMPs along with the ground truth measurements. In addition, in this study, factors affecting the accuracy of the calculation results are explored. The results of the estimated direct incident solar radiation show that the proposed method achieves the best accuracy, followed by the methods used in DOE-2, EnergyPlus, and DeST. The proposed method guarantees that the hourly direct solar insolation will remain the same and reflects the variation in the direct solar irradiance across a 1-h time frame. The proposed method can be adopted in BEMPs to improve the accuracy of the solar radiation calculation, thereby improving the accuracy of the simulated building performance and the BIPV production.

14 SOLAR ENERGY↗

Machine learning control of an elliptically bent hard x-ray mirror

This article showcases the high-resolution control of an elliptically bent hard X-ray mirror optics at the Advanced Photon Source. The mirror uses a compact laminar flexure bending mechanism to achieve elliptical shapes covering a large range of focal distances. An array of capacitive sensors are used as a surface profiler for in-situ monitoring of the mirror shape. Machine learning and control techniques were used to change the mirror shape and focus the incident X-ray at predefined focal planes. The mirror surface shape error can be controlled to be within 40 nm rms with high repeatability. This technique gives the capability to focus incident X-ray beam within a range of focal distances corresponding to shape deformation range of a mirror optics. This work would be beneficial for controlling similar adaptive optics for multiple adaptive optics systems.

adaptive optics↗

Measurement of the 239 Pu$(n, f$) prompt fission neutron spectrum from 10 keV to 10 MeV induced by neutrons of energy 1–20 MeV

Although the prompt fission neutron spectrum (PFNS) is an essential component of neutron-driven systems that has been measured for decades, there are still multiple glaring unknowns regarding the PFNS of major actinides in the fission neutron incident energy range, specifically with regard to multichance fission and pre-equilibrium neutron emission processes. The only impactful experimental 239 Pu PFNS measurements included in recent nuclear data evaluations were measured over a limited outgoing neutron energy range at thermal and 1.5-MeV average incident neutron energy, while other potentially impactful measurements have been shown to contain errors that resulted in either large uncertainty increases or in complete exclusion from nuclear data evaluation. Here, we report a measurement of the 239 Pu PFNS over a wide range of incident neutron energy (1–20 MeV) and three orders of magnitude in outgoing neutron energy (0.01–10 MeV) resulting from the Chi-Nu experiment at the Los Alamos Neutron Science Center. These results are the combination of separate PFNS measurements in the same experimental area, one using a Li-glass and the other a liquid scintillator detector array. Covariances between all PFNS data points from each detector and within each incident energy range were generated between all other data in both detector arrays and within all other incident neutron energy bins, yielding a single covariance matrix for all 1300 PFNS data points reported here. These covariances are based on a thorough assessment of systematic bias and uncertainties associated with the measurement, PFNS extraction technique, combination of data from each detector type, and other aspects of the analysis. The existence of covariances between PFNS data points in different incident neutron energy ranges yielded covariances between average PFNS energy values at each incident energy to be reported here as well, which allowed for firm statements to be made regarding a shape of a purely experimental mean PFNS energy trend for the first time. Although minor PFNS shape differences exist between the results reported here and recent nuclear data evaluations, the ENDF/B-VIII.0 and JEFF-3.3 PFNS evaluations agree reasonably well with the present results from 1-to 10-MeV incident neutron energy, which spans the well-measured 1.5-MeV incident neutron energy PFNS from Lestone and Shores as well as the onset of second-chance fission. However, while the pre-equilibrium component of the PFNS above 12-MeV incident neutron energy roughly agrees in position and magnitude with ENDF/B-VIII.0 and JEFF-3.3, clear differences relating to the relative magnitude of third-chance fission PFNS features are present in the PFNS shape and in the mean PFNS energy trends.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The impact of detection rate changes and correlations on random-coincidence background measurements

Coincidence detection of multiple particles emitted during an experiment can yield a new depth of understanding of the underlying process under study. However, the probability of detecting particles that are generated from the same physical event within a given coincidence time window is generally much lower than that of detecting particles that appear in the same coincidence time window, but were not created from the same physical event, and are therefore detected randomly in coincidence with each other. Thus, accurate and precise methods of measuring this random-coincidence background are essential for a wide variety of fields of science. A method to determine this background directly using the data themselves without any additional experimental run time or fake signals introduced in the data was recently established (O’Donnell, 2016). This method yields a statistical uncertainty on the random-coincidence background that is orders of magnitude smaller than that of the true coincidence data, though the potential for systematic errors of backgrounds from this method was never explored. In this work, we discuss common varieties of correlated and uncorrelated changes in the detection rates of each particle detected in an experiment. Here we demonstrate here that a correlation between particle detection rates from, for example, an incident particle beam that initiates a physical process of interest, creates systematic errors in the random-coincidence background measurement. We also discuss the impact of a variety of other realistic scenarios for rate changes in experiments. Lastly, a method is introduced to correct for errors in the random-coincidence background from any source, yielding an optimization between statistical precision and eliminating potential lingering systematic errors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Performance of the first mechanically-coupled twisting heliostat: encircled energy vs angle of incidence, and closed loop tracking

The first automatic twisting heliostat, with 8 m2 reflector, was completed and tested on-sun in January 2024. It was set up on a target-oriented dual-axis mount, with the target-axis aimed at a target 113 m to the west. The shape-twisting is purely automatic, made by a mechanical cam coupling to the cross-axis, which turns as the angle of incidence of the sun’s rays on the reflector. Three unsaturated images taken at different times of day were recorded of the sun on the target, reflected at angles of incidence of 5°, 49° and 68°. The measured FWHM of three images is very similar, about 1.09 m or 9.5 mrad, only slightly larger than an ideal solar disc, indicating that the different twisted reflector shapes are close to the ideal biconics needed to image the sun. The encircled energy measured for all three images was similar, 87% within approximately 1.30 m diameter. We report here also on a novel, tracking camera that employs a semitransparent beamsplitter fixed perpendicular to the mirror surface and to the plane of incidence. Over 2.5 hours of measurement of closed loop tracking, errors were ≤ 0.36 mrad rms, in both tracking axes.

14 SOLAR ENERGY↗

Measurement of Telescope Transmission Using a Collimated Beam Projector

With the increasingly large number of Type Ia supernova being detected by current-generation survey telescopes, and even more expected with the upcoming Rubin Observatory Legacy Survey of Space and Time, the precision of cosmological measurements will become limited by systematic uncertainties in flux calibration rather than statistical noise. One major source of systematic error in determining SNe Ia color evolution (needed for distance estimation) is uncertainty in telescope transmission, both within and between surveys. We introduce here the Collimated Beam Projector (CBP), which is meant to measure a telescope transmission with collimated light. The collimated beam more closely mimics a stellar wave front as compared to flat-field-based instruments, allowing for more precise handling of systematic errors such as those from ghosting and filter angle-of-incidence dependence. As a proof of concept, we present CBP measurements of the StarDICE prototype telescope, achieving a standard (1σ) uncertainty of 3% on average over the full wavelength range measured with a single beam illumination.

79 ASTRONOMY AND ASTROPHYSICS↗

AI-Optimized Polarization at Jefferson Lab

The AI-Optimized Polarization project seeks to develop experimental control applications for polarized targets and beams at Jefferson Lab using AI/ML. This paper will focus on two ongoing efforts involving a cryogenic polarized target and a linearly-polarized photon beam. Firstly, cryogenic targets, such as those used in Halls B and C (and approved for Hall D), are complex systems that are sensitive to a number of factors, including the temperature, beam currents, and the microwave and NMR apparatus. Secondly, the Hall D photon beam polarization depends on the optimal orientation of a diamond radiator, which produces coherent bremsstrahlung radiation from the electron beam incident upon it. Manual operation of both systems is tedious and error prone; implementing well-designed, interpretable control systems that incorporate AI is expected to lead to improved real-time polarization. AI optimization of nuclear physics experiments will lead, not just to cost-savings, but also to more efficient and higher-quality data, and this project will help to lay the foundation for future autonomous experiments.

Moran, Patrick [College of William and Mary, Willi↗

Investigating lab-scaled offshore wind aerodynamic testing failure and developing solutions for early anomaly detections

As offshore wind systems become more complex, the risk of human error or equipment malfunction increases during experimental testing. This study investigates a lab-scale incident involving a 1 : 50 scale 5 MW wind turbine, where a generator failure led to rotor overspeed and a blade–tower strike. To improve early fault detection, we propose a data-driven method based on multivariate long short-term memory (LSTM) models. High-frequency measurements are projected onto principal components, and anomalies are identified using reconstruction error and its time derivative. Two models are trained on different healthy datasets and tested using single- and multi-principal component (1PC and MPC) variations. Results show that combining both error and error derivative improves detection accuracy. The 1PC model detects faults faster, has a higher recall rate, and achieves a 43 % improvement in anomaly detection accuracy, while the MPC model yields higher precision. This approach provides a simple and effective tool for early anomaly detection in lab-scale experiments, helping to reduce the risk of future failures during the testing of new technologies.

17 WIND ENERGY↗

Measuring and modeling soil moisture and runoff at solar farms using a disconnected impervious surface approach

Abstract Ground‐mounted photovoltaic sites are often treated as impervious surfaces in stormwater permits. This ignores the pervious soils beneath and between solar arrays and leads to an overestimation of runoff. Our objective was to improve solar farm stormwater hydrology models by explicitly considering the disconnected impervious nature of solar design and site characteristics. Experimental sites established on utility scale solar farms in Colorado, Georgia, Minnesota, New York, and Oregon had perennial vegetative plantings with mean precipitation ranging from 40.6 to 124.5 cm, and soil texture ranging from loamy sand to clay. Soil moisture measurements were collected beneath arrays, under drip edges, and in the vegetated area between arrays at each site. Hydrus‐3D models for soil moisture and stormwater hydrology were developed that accounted for precipitation falling on solar panels, drip edge redistribution of rainfall, infiltration, and runoff in the pervious areas between solar arrays and beneath panels. Drip edge runoff averaged 3‐ to 10‐times incident precipitation at the New York and Minnesota sites, respectively. Root mean square error values between measured sub‐hourly soil moisture and predicted moisture for large measured single storm events averaged 0.029 across all five sites. Predicted runoff depths were strongly affected by precipitation depth, soil texture, soil profile depth, and soil bulk density. Runoff depths across the five experimental sites averaged 13%, 25%, and 45% of the 2‐, 10‐, and 100‐year design storm depths, clearly showing that these solar farms do not behave like impervious surfaces, but rather as disconnected impervious surfaces with substantial infiltration of runoff in the vegetated areas between and beneath solar arrays.

Agriculture↗

Adaptive shape control of wavefront-preserving X-ray mirrors with active cooling and heating

This article describes the development and testing of a novel, water cooled, active optic mirror system (called “REAL: Resistive Element Adjustable Length”) that combines cooling with applied auxiliary heating, tailored to the spatial distribution of the thermal load generated by the incident beam. This technique is theoretically capable of sub-nanometer surface figure error control even at high power density. Tests conducted in an optical metrology laboratory and at synchrotron X-ray beamlines showed the ability to maintain the mirror profile to the level needed for the next generation storage rings and FEL mirrors.

42 ENGINEERING↗