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At least 73 records · Page 4

Changes in the Economic Value of Variable Generation at High Penetration Levels: A Pilot Case Study of California

We estimate the long-run economic value of variable renewable generation with increasing penetration using a unique investment and dispatch model that captures long-run investment decisions while also incorporating detailed operational constraints and hourly time resolution over a full year. High time resolution and the incorporation of operational constraints are important for estimating the economic value of variable generation, as is the use of a modeling framework that accommodates new investment decisions. The model is herein applied with a case study that is loosely based on California in 2030. Increasing amounts of wind, photovoltaics (PV), and concentrating solar power (CSP) with and without thermal energy storage (TES) are added one at a time. The marginal economic value of these renewable energy sources is estimated and then decomposed into capacity value, energy value, day-ahead forecast error cost, and ancillary services. The marginal economic value, as defined here, is primarily based on the combination of avoided capital investment cost and avoided variable fuel and operations and maintenance costs from other power plants in the power system. Though the model only captures a subset of the benefits and costs of renewable energy, it nonetheless provides unique insights into how the value of that subset changes with technology and penetration level. Specifically, in this case study implementation of the model, the marginal economic value of all three solar options is found to exceed the value of a flat-block of power (as well as wind energy) by \$20--30/MWh at low penetration levels, largely due to the high capacity value of solar at low penetration. Because the value of CSP per unit of energy is found to be high with or without thermal energy storage at low penetration, we find little apparent incremental value to thermal storage at low solar penetration in the present case study analysis. The marginal economic value of PV and CSP without thermal storage is found to drop considerably (by more than \$70/MWh) as the penetration of solar increases toward 30\percent on an energy basis. This is due primarily to a steep drop in capacity value followed by a decrease in energy value. In contrast, the value of CSP with thermal storage drops much less dramatically as penetration increases. As a result, at solar penetration levels above 10\percent, CSP with thermal storage is found to be considerably more valuable relative to PV and CSP without thermal storage. The marginal economic value of wind is found to be largely driven by energy value, and is lower than solar at low penetration. The marginal economic value of wind drops at a relatively slower rate with penetration, however. As a result, at high penetration, the value of wind can exceed the value of PV and CSP without thermal storage. Though some of these findings may be somewhat unique to the specific case study presented here, the results: (1) highlight the importance of an analysis framework that addresses long-term investment decisions as well as short-term dispatch and operational constraints, (2) can help inform long-term decisions about renewable energy procurement and supporting infrastructure, and (3) point to areas where further research is warranted.

14 SOLAR ENERGY↗

Magellan/M2FS Spectroscopy of Galaxy Clusters: Stellar Population Model and Application to Abell 267

We report the results of a pilot program to use the Magellan/M2FS spectrograph to survey the galactic populations and internal kinematics of galaxy clusters. For this initial study, we present spectroscopic measurements for 223 quiescent galaxies observed along the line of sight of the galaxy cluster Abell 267 (z∼0.23). We develop a Bayesian method for modeling the integrated light from each galaxy as a simple stellar population, with free parameters that specify the redshift (v{sub los}/c) and characteristic age, metallicity ([Fe/H]), alpha-abundance ([α/Fe]), and internal velocity dispersion (σ{sub int}) for individual galaxies. Parameter estimates derived from our 1.5 hr observation of A267 have median random errors of σ{sub v{sub l{sub o{sub s}}}}=20 km s{sup −1}, σ{sub Age}=1.2 Gyr, σ{sub [Fe/H]}=0.11 dex, σ{sub [α/Fe]}=0.07 dex, and σ{sub σ{sub i{sub n{sub t}}}}=20 km s{sup −1}. In a companion paper, we use these results to model the structure and internal kinematics of A267.

79 ASTRONOMY AND ASTROPHYSICS↗

Tycho- Gaia Astrometric Solution Parallaxes and Proper Motions for Five Galactic Globular Clusters

We present a pilot study of Galactic globular cluster (GC) proper motion (PM) determinations using Gaia data. We search for GC stars in the Tycho- Gaia Astrometric Solution (TGAS) catalog from Gaia Data Release 1 (DR1), and identify five members of NGC 104 (47 Tucanae), one member of NGC 5272 (M3), five members of NGC 6121 (M4), seven members of NGC 6397, and two members of NGC 6656 (M22). By taking a weighted average of member stars, fully accounting for the correlations between parameters, we estimate the parallax (and, hence, distance) and PM of the GCs. This provides a homogeneous PM study of multiple GCs based on an astrometric catalog with small and well-controlled systematic errors and yields random PM errors similar to existing measurements. Detailed comparison to the available Hubble Space Telescope ( HST ) measurements generally shows excellent agreement, validating the astrometric quality of both TGAS and HST . By contrast, comparison to ground-based measurements shows that some of those must have systematic errors exceeding the random errors. Our parallax estimates have uncertainties an order of magnitude larger than previous studies, but nevertheless imply distances consistent with previous estimates. By combining our PM measurements with literature positions, distances, and radial velocities, we measure Galactocentric space motions for the clusters and find that these also agree well with previous analyses. Our analysis provides a framework for determining more accurate distances and PMs of Galactic GCs using future Gaia data releases. This will provide crucial constraints on the near end of the cosmic distance ladder and provide accurate GC orbital histories.

79 ASTRONOMY AND ASTROPHYSICS↗

What, why and when to go virtual: An international analysis of early adopters of virtual building energy codes inspections

To meet greenhouse gas reduction targets, several countries are pursuing more ambitious policies in their buildings and construction sectors, such as introducing zero net energy/carbon building codes. Countries often report not having enough qualified staff for performing building energy code inspections and many are exploring faster, easier, and more reliable methods to check the compliance of buildings with their codes. Building inspections are a critical element for ensuring code compliance and they have traditionally been performed in person. However, in-person inspections can be labor and travel intensive, costly, and prone to human error. In this paper, the authors explore how virtual inspections, particularly in light of the recent COVID-19 pandemic, have impacted processes for building code compliance checks in jurisdictions and communities around the world. Here, the authors collected data on four key parameters (time and financial savings, scope of inspections, changing practices and technological innovation, and benefits to consumers) from six jurisdictions and communities in five countries (Australia, Canada, Singapore, United Arab Emirates, and the United States) to analyze the impacts of virtual inspections on code compliance checks. The analysis found the greatest value from virtual inspections in geographically dispersed regions and for cities experiencing rapid building construction. The study also explored emerging technologies that are being piloted for virtual inspections. Although many of these technologies hold promise, more resources and capacity are needed to make them viable for use in building energy code inspections.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Enhanced Optical Head Tracking for Cranial Radiation Therapy: Supporting Surface Registration by Cutaneous Structures

Purpose: To support surface registration in cranial radiation therapy by structural information. The risk for spatial ambiguities is minimized by using tissue thickness variations predicted from backscattered near-infrared (NIR) light from the forehead. Methods and Materials: In a pilot study we recorded NIR surface scans by laser triangulation from 30 volunteers of different skin type. A ground truth for the soft-tissue thickness was segmented from MR scans. After initially matching the NIR scans to the MR reference, Gaussian processes were trained to predict tissue thicknesses from NIR backscatter. Moreover, motion starting from this initial registration was simulated by 5000 random transformations of the NIR scan away from the MR reference. Re-registration to the MR scan was compared with and without tissue thickness support. Results: By adding prior knowledge to the backscatter features, such as incident angle and neighborhood information in the scanning grid, we showed that tissue thickness can be predicted with mean errors of <0.2 mm, irrespective of the skin type. With this additional information, the average registration error improved from 3.4 mm to 0.48 mm by a factor of 7. Misalignments of more than 1 mm were almost thoroughly (98.9%) pushed below 1 mm. Conclusions: For almost all cases tissue-enhanced matching achieved better results than purely spatial registration. Ambiguities can be minimized if the cutaneous structures do not agree. This valuable support for surface registration increases tracking robustness and avoids misalignment of tumor targets far from the registration site.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SU-C-BRD-05: Non-Invasive in Vivo Biodosimetry in Radiotherapy Patients Using Electron Paramagnetic Resonance (EPR) Spectroscopy

Purpose: Medical intervention following a major, unplanned radiation event can elevate the human whole body exposure LD50 from 3 to 7 Gy. On a large scale, intervention cannot be achieved effectively without accurate and efficient triage. Current methods of retrospective biodosimetry are restricted in capability and applicability; published human data is limited. We aim to further develop, validate, and optimize an automated field-deployable in vivo electron paramagnetic resonance (EPR) instrument that can fill this need. Methods: Ionizing radiation creates highly-stable, carbonate-based free radicals within tooth enamel. Using a process similar to nuclear magnetic resonance, EPR directly measures the presence of radiation-induced free radicals. We performed baseline EPR measurements on one of the upper central incisors of total body irradiation (TBI) and head and neck (H&N) radiotherapy patients before their first treatment. Additional measurements were performed between subsequent fractions to examine the EPR response with increasing radiation dose. Independent dosimetry measurements were performed with optically-stimulated luminescent dosimeters (OSLDs) and diodes to more accurately establish the relationship between EPR signal and delivered radiation dose. Results: 36 EPR measurements were performed over the course of four months on two TBI and four H & N radiotherapy patients. We observe a linear increase in EPR signal with increasing dose across the entirety of the tested range. A linear least squares-weighted fit of delivered dose versus measured signal amplitude yields an adjusted R-square of 0.966. The standard error of inverse prediction (SEIP) is 1.77 Gy. For doses up to 7 Gy, the range most relevant to triage, we calculate an SEIP of 1.29 Gy. Conclusion: EPR spectroscopy provides a promising method of retrospective, non-invasive, in vivo biodosimetry. Our preliminary data show an excellent correlation between predicted signal amplitude and delivered dose. With further development, a robust means of predicting delivered radiation dose from EPR measurements is expected. This project was funded by the Biomedical Advanced Research and Development Authority (BARDA) within the U.S. Department of Health and Human Services subcontracted through the Geisel School of Medicine at Dartmouth and by the Dartmouth Physically-Based Biodosimetry Center for Medical Countermeasures Against Radiation (Dart-Dose CMCR) Pilot Program.

60 APPLIED LIFE SCIENCES↗

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗

Advanced Outage and Control Center: Strategies for Nuclear Plant Outage Work Status Capabilities

The research effort is a part of the Light Water Reactor Sustainability (LWRS) Program. LWRS is a research and development program sponsored by the Department of Energy, performed in close collaboration with industry to provide the technical foundations for licensing and managing the long-term, safe and economical operation of current nuclear power plants. The LWRS Program serves to help the US nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of the plants and extension of the current operating licenses. The Outage Control Center (OCC) Pilot Project was directed at carrying out the applied research for development and pilot of technology designed to enhance safe outage and maintenance operations, improve human performance and reliability, increase overall operational efficiency, and improve plant status control. Plant outage management is a high priority concern for the nuclear industry from cost and safety perspectives. Unfortunately, many of the underlying technologies supporting outage control are the same as those used in the 1980’s. They depend heavily upon large teams of staff, multiple work and coordination locations, and manual administrative actions that require large amounts of paper. Previous work in human reliability analysis suggests that many repetitive tasks, including paper work tasks, may have a failure rate of 1.0E-3 or higher (Gertman, 1996). With between 10,000 and 45,000 subtasks being performed during an outage (Gomes, 1996), the opportunity for human error of some consequence is a realistic concern. Although a number of factors exist that can make these errors recoverable, reducing and effectively coordinating the sheer number of tasks to be performed, particularly those that are error prone, has the potential to enhance outage efficiency and safety. Additionally, outage management requires precise coordination of work groups that do not always share similar objectives. Outage managers are concerned with schedule and cost, union workers are concerned with performing work that is commensurate with their trade, and support functions (safety, quality assurance, and radiological controls, etc.) are concerned with performing the work within the plants controls and procedures. Approaches to outage management should be designed to increase the active participation of work groups and managers in making decisions that closed the gap between competing objectives and the potential for error and process inefficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An approach to estimating flame radiation in combustion chambers containing suspended-particles

Thermal radiation often plays a key role in heat transfer between flames and the surrounding environment. Therefore, reliable measurement of flame radiation is indispensable in the study of combustion. While the measurement of radiative flux from flames is straightforward in an open environment, it is challenging to do so in a confined chamber, due to the influence of the walls. Radiation emitted by the walls and the reflection of flame radiation off the walls can interfere with measurements of flame radiation. For wall surfaces that are at high temperature or highly reflective, the error in the flame radiation measurement can be significant. Here in this paper, a theoretical analysis was carried out to study the contribution of wall emission and wall reflection to the incident radiation measured by radiometers. The results reveal that for a typical lab-scale air-fired flame, the contribution of wall emission and wall reflection to the measured incident radiation can be as high as 55% for a refractory-lined wall and 40% for a water-cooled wall. A convenient approach is proposed to distinguish flame radiation from the measured incident radiation. The approach is based on measurements of surface incident radiation and net radiative heat flux through the wall. The approach can be applied to optically thin systems (most lab-scale and some pilot-scale atmospheric pressure combustion systems) and optically dense systems (typically pressurized large-scale combustion systems). CFD simulations were also performed for two coal-fired combustors, one which represents optically thin and the other optically thick systems, to validate the theoretical model and the approach to estimating flame radiation. Good agreement was observed between CFD results and the theoretical model results, and the proposed approach to estimation of flame radiation was found to have reasonable accuracy.

42 ENGINEERING↗

A high precision instrument to measure angular and binocular deviation introduced by aircraft windscreens by using a shadow casting technique

Objects viewed through transparent sheets with residual non-parallelism and irregularity appear shifted and distorted. This distortion is measured in terms of angular and binocular deviation of an object viewed through the transparent sheet. The angular and binocular deviations introduced are particularly important in the context of aircraft windscreens and canopies as they can interfere with decision making of pilots especially while landing, leading to accidents. In this work, we have developed an instrument to measure both the angular and binocular deviations introduced by transparent sheets. This instrument is especially useful in the qualification of aircraft windscreens and canopies. It measures the deviation in the geometrical shadow cast by a periodic dot pattern trans-illuminated by the distorted light beam from the transparent test specimen compared to the reference pattern. Accurate quantification of the shift in the pattern is obtained by cross-correlating the reference shadow pattern with the specimen shadow pattern and measuring the location of the correlation peak. The developed instrument is handy to use and computes both angular and binocular deviation with an accuracy of less than {+-}0.1 mrad ( Almost-Equal-To 0.036 mrad) and has an excellent repeatability with an error of less than 2%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Light Water Reactor Sustainability Program: Digital Architecture Project Plan

There are many technologies available to the nuclear power industry to improve efficiency in plant work activities. These range from new control room technologies to those for mobile field workers. They can make a positive impact on a wide range of performance objectives – increase in productivity, human error reduction, validation of results, accurate transfer of data, and elimination of repetitive tasks. It is expected that the industry will more and more turn to these technologies to achieve these operational efficiencies to lower costs. At the same time, this will help utilities manage a looming staffing problem as the inevitable retirement wave of the more seasoned workers affects both staffing levels and knowledge retention. A barrier to this wide-scale implementation of new technologies for operational efficiency is the lack of a comprehensive digital architecture that can support the real-time information exchanges needed to achieve the desired operational efficiencies. This project will define an advanced digital architecture that will accommodate the entire range of system, process, and plant worker activity to enable the highest degree of integration, thereby creating maximum efficiency and productivity. This pilot project will consider a range of open standards that are suitable for the various data and communication requirements of a seamless digital environment. It will map these standards into an overall architecture to support the II&C developments of this research program.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Assimilation of a Coordinated Fleet of Uncrewed Aircraft System Observations in Complex Terrain: EnKF System Design and Preliminary Assessment

Abstract Uncrewed aircraft system (UAS) observations collected during the 2018 Lower Atmospheric Process Studies at Elevation—a Remotely Piloted Aircraft Team Experiment (LAPSE-RATE) field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting Model using an ensemble Kalman filter. The benefit of UAS observations was assessed for a terrain-driven (drainage and upvalley) flow event that occurred within Colorado’s San Luis Valley (SLV) using independent observations. The analysis and prediction of the strength, depth, and horizontal extent of drainage flow from the Saguache Canyon and the subsequent transition to upvalley and up-canyon flow were improved relative to that obtained both without data assimilation (benchmark) and when only surface observations were assimilated. Assimilation of UAS observations greatly improved the analyses of vertical variations in temperature, relative humidity, and winds at multiple locations in the northern portion of the SLV, with reductions in both bias and the root-mean-square error of roughly 40% for each variable relative to the benchmark run. Despite these noted improvements, some biases remain that were tied to measurement error and/or the impact of the boundary layer parameterization on vertically spreading the observations, both of which require further exploration. The results presented here highlight how observations obtained with a fleet of profiling UAS improve limited-area, high-resolution analyses and short-term forecasts in complex terrain.

54 ENVIRONMENTAL SCIENCES↗

Demonstrating high-precision, multiband transit photometry with MuSCAT: A case for HAT-P-14B

The Multicolor Simultaneous Camera for studying Atmospheres of Transiting exoplanets (MuSCAT) is an optical three-band (g{sub 2}{sup ′}-, r{sub 2}{sup ′}- and z{sub s,2}-band) imager that was recently developed for the 188 cm telescope at Okayama Astrophysical Observatory with the aim of validating and characterizing transiting planets. In a pilot observation with MuSCAT we observed a primary transit of HAT-P-14b, a high-surface gravity (g{sub p} = 38 ms{sup −2}) hot Jupiter around a bright (V = 10) F-type star. From a 2.9 hr observation we achieved the five-minute binned photometric precisions of 0.028%, 0.022%, and 0.024% in the g{sub 2}{sup ′}, r{sub 2}{sup ′}, and z{sub s,2} bands, respectively, which provided the highest-quality photometric data for this planet. Combining these results with those of previous observations, we search for variations of transit timing and duration over five years as well as variations of planet-star radius ratio (R{sub p}/R{sub s}) with wavelengths, but can find no considerable variation in any parameters. On the other hand, using the transit-subtracted light curves we simulate the achievable measurement error of R{sub p}/R{sub s} with MuSCAT for various planetary sizes, assuming three types of host stars: HAT-P-14, the nearby K-dwarf HAT-P-11, and the nearby M-dwarf GJ1214. Comparing our results with the expected atmospheric scale heights, we find that MuSCAT is capable of probing the atmospheres of planets as small as a sub-Jupiter (R{sub p}∼6R{sub ⊕}) around HAT-P-14 in all bands, a Neptune (∼4R{sub ⊕}) around HAT-P-11 in all bands, and a super-Earth (∼2.5R{sub ⊕}) around GJ1214 in r{sub 2}{sup ′} and z{sub s,2} bands. These results promise that MuSCAT will produce fruitful scientific outcomes in the K2 and TESS era.

79 ASTRONOMY AND ASTROPHYSICS↗

A Pilot Evaluation of a 4-Dimensional Cone-Beam Computed Tomographic Scheme Based on Simultaneous Motion Estimation and Image Reconstruction

Purpose: To evaluate the performance of a 4-dimensional (4-D) cone-beam computed tomographic (CBCT) reconstruction scheme based on simultaneous motion estimation and image reconstruction (SMEIR) through patient studies. Methods and Materials: The SMEIR algorithm contains 2 alternating steps: (1) motion-compensated CBCT reconstruction using projections from all phases to reconstruct a reference phase 4D-CBCT by explicitly considering the motion models between each different phase and (2) estimation of motion models directly from projections by matching the measured projections to the forward projection of the deformed reference phase 4D-CBCT. Four lung cancer patients were scanned for 4 to 6 minutes to obtain approximately 2000 projections for each patient. To evaluate the performance of the SMEIR algorithm on a conventional 1-minute CBCT scan, the number of projections at each phase was reduced by a factor of 5, 8, or 10 for each patient. Then, 4D-CBCTs were reconstructed from the down-sampled projections using Feldkamp-Davis-Kress, total variation (TV) minimization, prior image constrained compressive sensing (PICCS), and SMEIR. Using the 4D-CBCT reconstructed from the fully sampled projections as a reference, the relative error (RE) of reconstructed images, root mean square error (RMSE), and maximum error (MaxE) of estimated tumor positions were analyzed to quantify the performance of the SMEIR algorithm. Results: The SMEIR algorithm can achieve results consistent with the reference 4D-CBCT reconstructed with many more projections per phase. With an average of 30 to 40 projections per phase, the MaxE in tumor position detection is less than 1 mm in SMEIR for all 4 patients. Conclusion: The results from a limited number of patients show that SMEIR is a promising tool for high-quality 4D-CBCT reconstruction and tumor motion modeling.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Flexible Stellarator Physics Facility

We propose to build a Flexible Stellarator Physics Facility to explore promising regions of the vast parameter space of disruption-free stellarator solutions for Fusion Pilot Plants (FPPs). The FESAC Long Range Plan recognized the quasi-symmetric stellarator as “the leading US approach to developing disruption-free, low-recirculating-power fusion configurations”. To deliver the ambitious Decadal Vision for Commercial Fusion Energy, we must establish a persuasive stellarator program in parallel to the tokamak one: the stellarator will prove to be a better path to a reactor if theoretical predictions are confirmed and novel optimization techniques and strategies work as desired. Since the release of the Long Range Plan in 2020, stellarators have arguably made the most significant advances of all fusion concepts. Groundbreaking results from W7-X demonstrated low neoclassical transport and the successful operation of the island divertor. Advances in theory and modeling now allow us to minimize turbulent transport, to achieve equilibria with precise quasisymmetry, to reduce neoclassical transport and fast ion loss to levels far below what has been previously achieved, and to minimize the effect of coil manufacturing errors. If realized, these advances will lead to cost-effective stellarator designs with confinement comparable to tokamaks but without the fundamental challenges of disruptions and current drive.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Wireless Underground Sensor Network Field Pilot for Agriculture and Ecology: Soil Moisture Mapping Using Signal Attenuation

Wireless Underground Sensor Networks (WUSNs) that collect geospatial in situ sensor data are a backbone of internet-of-things (IoT) applications for agriculture and terrestrial ecology. In this paper, we first show how WUSNs can operate reliably under field conditions year-round and at the same time be used for determining and mapping soil conditions from the buried sensor nodes. We demonstrate the design and deployment of a 23-node WUSN installed at an agricultural field site that covers an area with a 530 m radius. The WUSN has continuously operated since September 2019, enabling real-time monitoring of soil volumetric water content (VWC), soil temperature (ST), and soil electrical conductivity. Secondly, we present data collected over a nine-month period across three seasons. We evaluate the performance of a deep learning algorithm in predicting soil VWC using various combinations of the received signal strength (RSSI) from each buried wireless node, above-ground pathloss, the distance between wireless node and receive antenna (D), ST, air temperature (AT), relative humidity (RH), and precipitation as input parameters to the model. The AT, RH, and precipitation were obtained from a nearby weather station. We find that a model with RSSI, D, AT, ST, and RH as inputs was able to predict soil VWC with an R 2 of 0.82 for test datasets, with a Root Mean Square Error of ±0.012 (m 3 /m 3 ). Hence, a combination of deep learning and other easily available soil and climatic parameters can be a viable candidate for replacing expensive soil VWC sensors in WUSNs.

47 OTHER INSTRUMENTATION↗

A Scalable Reduced‐Order Model for the Steady Navier–Stokes Equations

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional numerical methods are computationally intractable even for intermediate pilot plant scales. Recently, the component reduced order modeling method has been developed to tackle this challenge by combining projection reduced order modeling and discontinuous Galerkin domain decomposition. However, while many scientific or engineering applications involve nonlinear physics, this method has only been demonstrated for various linear systems. In this work, the component reduced order modeling method is extended to steady Navier–Stokes flow, with application to general nonlinear physics in view. The large‐scale, global domain is decomposed into a combination of small‐scale unit component. Linear subspaces for flow velocity and pressure are identified via proper orthogonal decomposition over sample snapshots collected from each small‐scale unit component. Velocity bases are augmented with a pressure supremizer to satisfy the inf–sup condition for stable pressure prediction. Two different nonlinear reduced order modeling methods are employed and compared for efficient evaluation of nonlinear advection: A third‐order tensor projection operator and the empirical quadrature procedure. The proposed method is demonstrated on the flow over arrays of five different unit objects, achieving a 23‐fold speedup with less than 4% relative error in domains up to 256 times larger than the unit components. Furthermore, a numerical experiment with the pressure supremizer strongly indicates the need for a supremizer for stable pressure prediction. A comparison between the tensorial approach and the empirical quadrature procedure revealed a slight advantage of the empirical quadrature procedure. The framework is compared with an alternating Schwarz‐based reduced‐order approach, demonstrating improved efficiency and robustness for the DG‐based global solver while retaining flexibility for sub‐scale iterative solvers. The method is further extended to a coupled advection–diffusion and Navier–Stokes system, illustrating its applicability to multi‐physics problems and its potential for more general, inter‐coupled nonlinear systems.

42 ENGINEERING↗

SU-F-J-18: Feasibility of Open Mask Immobilization with Optical Imaging Guidance (OIG) for H&N Radiotherapy

Purpose: Full face and neck thermoplastic masks provide standard-of-care immobilization for patients receiving H&N IMRT. However, these masks are uncomfortable and increase skin dose. The purpose of this pilot study was to investigate the feasibility and setup accuracy of open face and neck mask immobilization with OIG. Methods: Ten patients were consented and enrolled to this IRB-approved protocol. Patients were immobilized with open masks securing only forehead and chin. Standard IMRT to 60–70 Gy in 30 fractions were delivered in all cases. Patient simulation information, including isocenter location and CT skin contours, were imported to a commercial OIG system. On the first day of treatment, patients were initially set up to surface markings and then OIG referenced to face and neck skin regions of interest (ROI) localized on simulation CT images, followed by in-room CBCT. CBCTs were acquired at least weekly while planar OBI was acquired on the days without CBCT. Following 6D robotic couch correction with kV imaging, a new optical real-time surface image was acquired to track intrafraction motion and to serve as a reference surface for setup at the next treatment fraction. Therapists manually recorded total treatment time as well as couch shifts based on kV imaging. Intrafractional ROI motion tracking was automatically recorded. Results: Setup accuracy of OIG was compared with CBCT results. The setup error based on OIG was represented as a 6D shift (vertical/longitudinal/lateral/rotation/pitch/roll). Mean error values were −0.70±3.04mm, −0.69±2.77mm, 0.33±2.67 mm, −0.14±0.94 o, −0.15±1.10o and 0.12±0.82o, respectively for the cohort. Average treatment time was 24.1±9.2 minutes, comparable to standard immobilization. The amplitude of intrafractional ROI motion was 0.69±0.36 mm, driven primarily by respiratory neck motion. Conclusion: OGI can potentially provide accurate setup and treatment tracking for open face and neck immobilization. Study accrual and patient/provider satisfaction survey collection remain ongoing. This study is supported by VisionRT, Ltd.

60 APPLIED LIFE SCIENCES↗