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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Transcriptomic analysis of skin pigmentation variation in the Virginia opossum ( Didelphis virginiana )

Abstract Skin pigmentation and coat pigmentation are two of the best‐studied examples of traits under natural selection given their quantifiable fitness interactions with the environment (e.g., camouflage) and signalling with other organisms (e.g., warning coloration). Previous morphological studies have found that skin pigmentation variation in the Virginia opossum ( Didelphis virginiana ) is associated with variation in precipitation and temperatures across its distribution range following Gloger's rule (lighter pigmentation in temperate environments). To investigate the molecular mechanism associated with skin pigmentation variation, we used RNA‐Seq and quantified gene expression of wild opossums from tropical and temperate populations. Using differential expression analysis and a co‐expression network approach, we found that expression variation in genes with melanocytic and immune functions is significantly associated with the degree of skin pigmentation variation and may be underlying this phenotypic difference. We also found evidence suggesting that the Wnt/β‐catenin signalling pathway might be regulating the depigmentation observed in temperate populations. Based on our study results, we present several alternative hypotheses that may explain Gloger's rule pattern of skin pigmentation variation in opossum, including changes in pathogen diversity supporting a pathogen‐resistant hypothesis, thermal stress associated with temperate environments, and pleiotropic and epistatic interactions between melanocytic and immune genes.

Nigenda‐Morales, Sergio F.↗
DOE OSTI2024

Enhancing risk and crisis communication with computational methods: A systematic literature review

Abstract Recent developments in risk and crisis communication (RCC) research combine social science theory and data science tools to construct effective risk messages efficiently. However, current systematic literature reviews (SLRs) on RCC primarily focus on computationally assessing message efficacy as opposed to message efficiency. We conduct an SLR to highlight any current computational methods that improve message construction efficacy and efficiency. We found that most RCC research focuses on using theoretical frameworks and computational methods to analyze or classify message elements that improve efficacy. For improving message efficiency, computational and manual methods are only used in message classification. Specifying the computational methods used in message construction is sparse. We recommend that future RCC research apply computational methods toward improving efficacy and efficiency in message construction. By improving message construction efficacy and efficiency, RCC messaging would quickly warn and better inform affected communities impacted by current hazards. Such messaging has the potential to save as many lives as possible.

Mathematical Methods In Social Sciences↗
DOE OSTI2022

THERMAL MODELING OF HANFORD LEAD CANISTER’S HEATER BENCH TESTS

A computational fluid dynamics (CFD) model was built to simulate planned testing of heater assemblies for the Hanford Lead Canister (HLC) project. The HLC is a canister storage system that will contain heaters to simulate the decay heat of nuclear material and provide the canister storage system with environmental conditions equivalent to the operating conditions on a dry storage pad. The HLC will be equipped with long-term data collection and monitoring systems to provide an early warning of corrosion, pitting, cracking, or other signs of canister degradation that might threaten the integrity of the containment boundary over the potentially long term of dry storage. An important part of the HLC development is to confirm the function and ability of the electric heater assemblies that were specially designed to provide heating similar to the decay heat of nuclear material contained within the canister storage system. Heater bench testing is planned for early 2022 in a test configuration that does not include the canister. The goal of the bench testing is to verify that the heaters can replicate the decay heat of a canister with nuclear material and to validate the thermal models, which are critical to understanding the HLC’s thermal environment, including the local air flow within the canister storage system. Testing of the heater assemblies inside the canister system are planned in the future to validate canister level thermal models, and rigorous pre-deployment testing of the complete HLC cask and canister system is intended to be completed before the HLC is deployed in the 2025-2026 timeframe. This study presents the pre-test temperature predictions of the bench testing. A description of the heater assemblies and planned bench testing is presented. The model was developed with the commercial CFD code STAR-CCM+. An uncertainty analysis was run with the CFD model to determine the uncertainty in the temperature predictions and provide a range over which the predicted temperatures are expected to vary. The uncertainty analysis was performed by coupling STAR-CCM+ with the software Dakota, which provides advanced parametric analyses, including quantification of margins and uncertainty with computational models. This work is expected to provide insight into SNF canister behavior.

Suffield, Sarah R.↗
DOE OSTI2024

THERMAL MODELING OF HANFORD CESIUM AND STRONTIUM CANISTERS DURING SIMULATED LOADING

A computational fluid dynamics (CFD) model was built to simulate planned testing of heater assemblies within a canister and overpack for the Hanford Lead Canister (HLC) project. The HLC is a canister storage system that will contain heaters to simulate the decay heat of nuclear material and provide the canister storage system with environmental conditions equivalent to the operating conditions on a dry storage pad. The HLC will be equipped with long-term data collection and monitoring systems to provide an early warning of corrosion, pitting, cracking, or other signs of canister degradation that might threaten the integrity of the containment boundary over the potentially long term of dry storage. An important part of the HLC development is to make pretest numerical predictions for the behavior of the heated canister during the simulated radiolytic decay heat testing, which simulates the dry storage system during loading operations. The simulated radiolytic decay heat test is planned for mid-2024 in a configuration that includes the heater assembly, overpack, and canister, but with the lids removed to allow loading cesium and strontium capsules into the canister. One of the goals of the test is to evaluate the thermal behavior of the canister and overpack assembly in the ambient air of the test facility, which will provide data critical to validating the thermal models and understanding how the HLC will perform as a system once deployed. To best approximate real-world conditions, the CFD model includes the full air volume of the mock-up truck bay the heated canister test will be performed in, enabling detailed investigation of how the heated canister affects airflow around it. Rigorous pre-deployment testing of the complete HLC cask and canister system is intended to be completed before the HLC is deployed in the 2028 timeframe. This study presents the pre-test temperature predictions of the simulated radiolytic decay heat test. A description of the heater assembly, canister, and overpack system is presented. The model was developed with the commercial CFD software STAR-CCM+. An uncertainty analysis was run with the CFD model to determine the uncertainty in the temperature predictions and provide a range over which the predicted temperatures are expected to vary. The uncertainty analysis was preformed by coupling STAR-CCM+ with the software Dakota, which provides advanced parametric analyses, including quantification of margins and uncertainty with computational models. This work is expected to provide insight into SNF canister behavior.

Carpenter-Graffy, Dina E.↗
DOE OSTI2016

MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection

Purpose: The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. Methods: Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contours were selected in a spectral clustering manifold learning framework. This aids in clustering “similar” gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. Results: A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). Conclusions: An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all gold seeds are either correctly detected or a warning is raised for further manual intervention.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-310: Does a Head-Mounted Ionization Chamber Detect IMRT Errors?

Purpose: The conventional plan verification strategy is delivering a plan to a QA-phantom before the first treatment. Monitoring each fraction of the patient treatment in real-time would improve patient safety. We evaluated how well a new detector, the IQM (iRT Systems, Germany), is capable of detecting errors we induced into IMRT plans of three different treatment regions. Results were compared to an established phantom. Methods: Clinical plans of a brain, prostate and head-and-neck patient were modified in the Pinnacle planning system, such that they resulted in either several percent lower prescribed doses to the target volume or several percent higher doses to relevant organs at risk. Unaltered plans were measured on three days, modified plans once, each with the IQM at an Elekta Synergy with an Agility MLC. All plans were also measured with the ArcCHECK with the cavity plug and a PTW semiflex 31010 ionization chamber inserted. Measurements were evaluated with SNC patient software. Results: Repeated IQM measurements of the original plans were reproducible, such that a 1% deviation from the mean as warning and 3% as action level as suggested by the manufacturer seemed reasonable. The IQM detected most of the simulated errors including wrong energy, a faulty leaf, wrong trial exported and a 2 mm shift of one leaf bank. Detection limits were reached for two plans - a 2 mm field position error and a leaf bank offset combined with an MU change. ArcCHECK evaluation according to our current standards also left undetected errors. Ionization chamber evaluation alone would leave most errors undetected. Conclusion: The IQM detected most errors and performed as well as currently established phantoms with the advantage that it can be used throughout the whole treatment. Drawback is that it does not indicate the source of the error.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-TeP4-11: Implementation of a Non-Measurement-Based Patient-Specific IMRT QA Program

Purpose: To implement a comprehensive non-measurement-based verification program for patient-specific IMRT QA Methods: Based on published guidelines, a robust IMRT QA program should assess the following components: 1) accuracy of dose calculation, 2) accuracy of data transfer from the treatment planning system (TPS) to the record-and-verify (RV) system, 3) treatment plan deliverability, and 4) accuracy of plan delivery. Results: We have implemented an IMRT QA program that consist of four components: 1) an independent re-calculation of the dose distribution in the patient anatomy with a commercial secondary dose calculation program: Mobius3D (Mobius Medical Systems, Houston, TX), with dose accuracy evaluation using gamma analysis, PTV mean dose, PTV coverage to 95%, and organ-at-risk mean dose; 2) an automated in-house-developed plan comparison system that compares all relevant plan parameters such as MU, MLC position, beam iso-center position, collimator, gantry, couch, field size settings, and bolus placement, etc. between the plan and the RV system; 3) use of the RV system to check the plan deliverability and further confirm using “mode-up” function on treatment console for plans receiving warning; and 4) implementation of a comprehensive weekly MLC QA, in addition to routine accelerator monthly and daily QA. Among 1200 verifications, there were 9 cases of suspicious calculations, 5 cases of delivery failure, no data transfer errors, and no failure of weekly MLC QA. These 9 suspicious cases were due to the PTV extending to the skin or to heterogeneity correction effects, which would not have been caught using phantom measurement-based QA. The delivery failure was due to the rounding variation of MLC position between the planning system and RV system. Conclusion: A very efficient, yet comprehensive, non-measurement-based patient-specific QA program has been implemented and used clinically for about 18 months with excellent results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-201-03: Automatic Pre-Delivery Verification Using Statistical Analysis of Consistencies in Treatment Plan Parameters by the Treatment Site and Modality

Purpose: A novel computer software system, namely APDV (Automatic Pre-Delivery Verification), has been developed for verifying patient treatment plan parameters right prior to treatment deliveries in order to automatically detect and prevent catastrophic errors. Methods: APDV is designed to continuously monitor new DICOM plan files on the TMS computer at the treatment console. When new plans to be delivered are detected, APDV checks the consistencies of plan parameters and high-level plan statistics using underlying rules and statistical properties based on given treatment site, technique and modality. These rules were quantitatively derived by retrospectively analyzing all the EBRT treatment plans of the past 8 years at authors’ institution. Therapists and physicists will be notified with a warning message displayed on the TMS computer if any critical errors are detected, and check results, confirmation, together with dismissal actions will be saved into database for further review. Results: APDV was implemented as a stand-alone program using C# to ensure required real time performance. Mean values and standard deviations were quantitatively derived for various plan parameters including MLC usage, MU/cGy radio, beam SSD, beam weighting, and the beam gantry angles (only for lateral targets) per treatment site, technique and modality. 2D-based rules of combined MU/cGy ratio and averaged SSD values were also derived using joint probabilities of confidence error ellipses. The statistics of these major treatment plan parameters quantitatively evaluate the consistency of any treatment plans which facilitates automatic APDV checking procedures. Conclusion: APDV could be useful in detecting and preventing catastrophic errors immediately before treatment deliveries. Future plan including automatic patient identify and patient setup checks after patient daily images are acquired by the machine and become available on the TMS computer. This project is supported by the Agency for Healthcare Research and Quality (AHRQ) under award 1R01HS0222888. The senior author received research grants from ViewRay Inc. and Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-201-09: Predicting Accelerator Dysfunction

Purpose: To develop an integrated statistical process control (SPC) framework using digital performance and component data accumulated within the accelerator system that can detect dysfunction prior to unscheduled downtime. Methods: Seven digital accelerators were monitored for twelve to 18 months. The accelerators were operated in a ‘run to failure mode’ with the individual institutions determining when service would be initiated. Institutions were required to submit detailed service reports. Trajectory and text log files resulting from a robust daily VMAT QA delivery were decoded and evaluated using Individual and Moving Range (I/MR) control charts. The SPC evaluation was presented in a customized dashboard interface that allows the user to review 525 monitored parameters (480 MLC parameters). Chart limits were calculated using a hybrid technique that includes the standard SPC 3σ limits and an empirical factor based on the parameter/system specification. The individual (I) grand mean values and control limit ranges of the I/MR charts of all accelerators were compared using statistical (ranked analysis of variance (ANOVA)) and graphical analyses to determine consistency of operating parameters. Results: When an alarm or warning was directly connected to field service, process control charts predicted dysfunction consistently on beam generation related parameters (BGP)– RF Driver Voltage, Gun Grid Voltage, and Forward Power (W); beam uniformity parameters – angle and position steering coil currents; and Gantry position accuracy parameter: cross correlation max-value. Control charts for individual MLC – cross correlation max-value/position detected 50% to 60% of MLCs serviced prior to dysfunction or failure. In general, non-random changes were detected 5 to 80 days prior to a service intervention. The ANOVA comparison of BGP determined that each accelerator parameter operated at a distinct value. Conclusion: The SPC framework shows promise. Long term monitoring coordinated with service will be required to definitively determine the effectiveness of the model. Varian Medical System, Inc. provided funding in support of the research presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

TH-CD-207A-02: Implementation of Live EPID-Based Inspiration Level Assessment (LEILA) for Deepinspiration Breath-Hold (DIBH) Monitoring Using MV Fluoroscopy

Purpose: As prior work has shown that current DIBH monitoring approaches using surrogate measures (marker block on chest) do not always correspond with the clinical quantity of interest (lung depth, LD), a software tool and workflow are introduced to use MV fluoroscopy during treatment for real-time / Live EPID-based Inspiration Level Assessment (LEILA). Methods: A prototype software tool calculates and displays the LD during the treatment of left sided breast cancer. Calculations are based on MV cine images which are acquired with the treatment beam thereby not incurring any additional imaging dose. Image capture and processing are implemented using a dedicated frame grabber computer. The calculation engine automatically detects image orientation and includes provisions for large treatment fields that exceed the size of the EPID panel. LD is measured along a line profile in the middle of the field. LEILA’s interface displays the current MV image, a reference image (DRR), the current LD, as well as a trace of LD over treatment time. The display includes patient specific LD tolerances. Tolerances are specified for each field and loaded before the treatment. A visual warning is generated when the tolerance is exceeded. LEILA is initially run in parallel with current DIBH techniques. When later run by itself DIBH setup will be done using skin marks and room laser. Results: Offline tests of LEILA confirmed accurate automatic LD measurement for a variety of patient geometries. Deployment of the EPID during all left sided breast treatments was well tolerated by patients and staff during a multi-month pilot. The frame grabber provides 11 frames-per-second; the MATLAB based LEILA prototype software can analyze five frames-per-second standalone on standard desktop hardware. Conclusion: LEILA provides an automated approach to quantitatively monitor LD on MV images during DIBH treatment. Future improvements include a database and further speed optimization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Building hypotheses to understand the synergistic effects of heat and pollution exposure in a changing climate

The increasing intensity, frequency, and duration of extreme weather events due to climate change poses a broad range of health risks, and the synergistic effects of extreme temperature co-occurring with other hazardous exposures such as air pollution may result in higher risks of all-cause mortality and cardiovascular and respiratory morbidity than exposure to either event alone. There are a number of hypothesized mechanisms for this interaction effect, including increased susceptibility to heat effects on chronic conditions affected by air pollution exposure, exacerbation of pollution effects due to temperature-induced stress, and shared pathophysiological pathways (e.g., systemic inflammation), but specific physiological mechanisms are not well understood. In this editorial, the authors discuss this aspect of a recently published study examining ambient formaldehyde combined with high temperature exposure and respiratory disease admissions among children. Here, the observation that the health effects of pollutants such as formaldehyde are amplified following periods of high temperature can help inform risk warning systems even without knowledge of the underlying physiological mechanisms, but a deeper biological understanding of the interaction effects of heat and ambient air pollution may better inform interventions. This is even more important in view of increases in both extreme temperature and pollution events tied to climate change.

Chambliss, Sarah [University of Texas at Austin, T↗
DOE OSTI2017

Design Science Methodology Applied to a Chemical Surveillance Tool

Public health surveillance systems gain significant benefits from integrating existing early incident detection systems,supported by closed data sources, with open source data.However, identifying potential alerting incidents relies on finding accurate, reliable sources and presenting the high volume of data in a way that increases analysts work efficiency; a challenge for any system that leverages open source data. In this paper, we present the design concept and the applied design science research methodology of ChemVeillance, a chemical analyst surveillance system.Our work portrays a system design and approach that translates theoretical methodology into practice creating a powerful surveillance system built for specific use cases.Researchers, designers, developers, and related professionals in the health surveillance community can build upon the principles and methodology described here to enhance and broaden current surveillance systems leading to improved situational awareness based on a robust integrated early warning system.

Huang, Zhuanyi↗
DOE OSTI2018

Sensalert: A Real-time Group and Individual Health Tracking Application

Sensalert is a wearable health tracking application that enables monitoring of a target population’s health status in real-time. The application integrates health monitoring parameters from wearable sensors, e.g., temperature and heart rate, with relevant environmental parameters, e.g., weather and topography, and calculates the corresponding physiological strain index for each point in time. The objective of this application is to provide early warning, support decision making, and increase situational awareness by displaying comprehensive information and providing alerts at the right time and place. This application is the first of its kind being developed for integration into the Defense Threat Reduction Agencies Bio Surveillance Ecosystem (BSVE). We present the user requirements and design principles for developing this type of application. We hope this work helps and inspires future research in the area of wearable technologies for surveillance.

Huang, Zhuanyi↗
DOE OSTI2018

LADR: low-cost application-level detector for reducing silent output corruptions

Applications running on future high performance computing (HPC) systems are more likely to experience transient faults due to technology scaling trends with respect to higher circuit density, smaller transistor size and near-threshold voltage (NTV) operations. A transient fault could corrupt application state without warning, possibly leading to incorrect application output. Such errors are called silent data corruptions (SDCs). In this paper, we present LADR, a low-cost application-level SDC detector for scientific applications. LADR protects scientific applications from SDCs by watching for data anomalies in their state variables (those of scientific interest). It employs compile-time data-flow analysis to minimize the number of monitored variables, thereby reducing runtime and memory overheads while maintaining a high level of fault coverage with low false positive rates. We evaluated LADR with 4 scientific workloads and results show that LADR achieved < 80% fault coverage with only ∼ 3% runtime overheads and ∼ 1% memory overheads. As compared to prior state-of-the-art anomaly-based detection methods, SDC achieved comparable or improved fault coverage, but reduced runtime overheads by 21% ∼ 75%, and memory overheads by 35% ∼ 55% for the evaluated workloads. We believe that such an approach with low memory and runtime overheads coupled with attractive detection precision makes LADR a viable approach for assuring the correct output from large-scale high performance simulations.

Chen, Chao↗
DOE OSTI2019

Using Social Media to Geo-Target Emergency Management Efforts

The ubiquity of social media data has increased their use during emergency management (EM) in near real-time. For instance, during Haiti Earthquake (2010) and Hurricane Harvey (2017), Ushahidi and Twitter were used respectively for emergency response and rescue operations. Nonetheless, social media data tend to contain [ir]relevant information to be useful for disaster analytics for EM efforts. In this study, geo-tagged tweets obtained for 2013 Colorado flooding were analyzed to determine (i) what kind of situational awareness (SA) information could be extracted from tweets for emergency response and (ii) what is the spatio-temporal distribution of such information. The results indicate that tweets generated before September 12th (day of heavy precipitation) were non-relevant, but tweets generated on and following September 12th contained crisis information (about the event and its impacts), warnings, preparatory information. Next phase of this study will focus on developing a framework to integrate SA information with physical risk and social vulnerability to geo-target EM efforts.

Kar, Bandana↗
DOE OSTI2020

Next-generation geospatial-temporal information technologies for disaster management

Traditional geographic information systems (GIS) have been disrupted by the emergence of Big Data in the form of geo-coded raster, vector, and time-series Internet-of-Things data. This article discusses the application of new scalable technologies that go far beyond relational databases and file-based storage on spinning disk or tape to incorporate both storage and processing data in the same platform. The roles of the Apache Hadoop Distributed File Systems and NoSQL key-value stores such as the Apache Hbase are discussed, along with indexing schemes that optimally support geospatial-temporal use. Here, we highlight how this new approach can rapidly search multiple GIS data layers to obtain insights in the context of early warning, impact evaluation, response, and recovery to earthquake and wildfire disasters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Electromagnetic Particle Injector for Fast Time Response Disruption Mitigation in Tokamaks

A novel, rapid time-response, disruption mitigation system referred to as the Electromagnetic Particle Injector (EPI) is described. This method can accurately deliver the radiative payload to the plasma center on a <10 ms time scale, much faster, and deeper, than what can be achieved using conventional methods. The EPI system accelerates a sabot electromagnetically. The sabot is a metallic capsule that can be accelerated to desired velocities by an electromagnetic impeller. At the end of its acceleration, within 2 ms, the sabot will release a radiative payload, which is composed of low-z granules, or a shell pellet containing smaller pellets. The primary advantage of the EPI concept over gas propelled systems is its potential to meet short warning time scales, while accurately delivering the required particle size and materials at the velocities needed for achieving the required penetration depth in high power ITER-scale discharges for thermal and runaway current disruption mitigation. The present experimental tests from a prototype system have demonstrated the acceleration of a 3.2 g sabot to over 150 m/s within 1.5 ms, consistent with the calculations, giving some degree of confidence that larger ITER-scale injector can be developed.

High velocity↗
DOE OSTI2019

Modelling of Ablatant Deposition from Electromagnetically Driven Radiative Pellets for Disruption Mitigation Studies

The Electromagnetic Particle Injector (EPI) concept is advanced through the simulation of ablatant deposition into ITER H-mode discharges with calculations showing penetration past the H-mode pedestal for a range of injection velocities and granule sizes concurrent with the requirements of disruption mitigation. As discharge stored energy increases in future fusion devices such as ITER, control and handling of disruption events becomes a critical issue. An unmitigated disruption could lead to failure of the plasma facing components resulting in financially and politically costly repairs. Methods to facilitate the quench of an unstable high current discharge are required. With the onset warning time for some ITER disruption events estimated to be less than 10 ms, a disruption mitigation system needs to be considered which operates at injection speeds greater than gaseous sound speeds. Such an actuator could then serve as a means to augment presently planned pneumatic injection systems. The EPI uses a rail gun concept whereby a radiative payload is delivered into the discharge by means of the JxB forces generated by an external current pulse, allowing for injection velocities in excess of 1 km/s. The present status of the EPI project is outlined, including the addition of boost magnetic coils. These coils augment the self-generated rail gun magnetic field and thus provide a more efficient acceleration of the payload. The coils and the holder designed to constrain them have been modelled with the ANSYS code to ensure structural integrity through the range of operational coil cu

disruption↗