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At least 235 records · Page 13

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NASA NTRS2023

Differential Saccade-Pursuit Coordination Under Sleep Loss and Low-Dose Alcohol

Introduction: Ocular tracking of a moving object requires tight coordination between smooth pursuit and saccadic eye movements. Normally, pursuit drives gaze velocity to closely match target velocity, with residual position offsets corrected by catch-up saccades. However, how/if common stressors affect this coordination is largely unknown. This study seeks to elucidate the effects of acute and chronic sleep loss, and low-dose alcohol, on saccade-pursuit coordination, as well as that of caffeine. Methods: We used an ocular tracking paradigm to assess three metrics of tracking (pursuit gain, saccade rate, saccade amplitude) and to compute “ground lost” (from reductions in steady-state pursuit gain) and “ground recouped” (from increases in steady-state saccade rate and/or amplitude). We emphasize that these are measures of relative changes in positional offsets, and not absolute offset from the fovea. Results: Under low-dose alcohol and acute sleep loss, ground lost was similarly large. However, under the former, it was nearly completely recouped by saccades, whereas under the latter, compensation was at best partial. Under chronic sleep restriction and acute sleep loss with a caffeine countermeasure, the pursuit deficit was dramatically smaller, yet saccadic behavior remained altered from baseline. In particular, saccadic rate remained significantly elevated, despite the fact that ground lost was minimal. Discussion: This constellation of findings demonstrates differential impacts on saccade-pursuit coordination with low-dose alcohol impacting only pursuit, likely through extrastriate cortical pathways, while acute sleep loss not only disrupts pursuit but also undermines saccadic compensation, likely through midbrain/brainstem pathways. Furthermore, while chronic sleep loss and caffeine-mitigated acute sleep loss show little residual pursuit deficit, consistent with uncompromised cortical visual processing, they nonetheless show an elevated saccade rate, suggesting residual midbrain and/or brainstem impacts.

smooth pursuit↗

NASA NTRSDate not supplied

Deletion of Cdkn1a in Mice Rescues Reduced Osteogenesis in Microgravity and Increases Coupled Osteoclastic Bone Degenerative Activity and Bone Loss

Elevated Cdkn1a/p21 levels in mouse bone during spaceflight have led us to hypothesize that this cell cycle inhibitor could regulate osteogenesis in response to mechanical unloading in microgravity. Cdkn1a interacts with cyclins CDK1/2/4,6 during G1 and S phases, and suppression of its expression by mechanical stretch enhances proliferation and mineralization in osteoblastic cell cultures. To test this hypothesis in a whole-organism model, we used C57BL/J6 WT/Cdkn1a-null mice in the NASA RR-10, 30-day ISS microgravity experiment. To quantify active mineralization in microgravity mice were injected with Calcein seven and two days before euthanasia on-orbit, followed by high-resolution confocal imaging of optically cleared femoral endosteal surfaces. To quantify cortical and cancellous bone parameters we conducted microCT analyses of the femur and tibia. Confocal imaging revealed a population of mineralizing calcein-positive single osteoblasts, and multicellular surfaces of mineralization by osteocytes in lacunae. The Cdkn1a-null genotype shows a greater ratio of early-osteoblasts to late-osteocytes and reduced mineralization versus WT. Additionally, in microgravity WT bones have a large (80%) decrease in active mineralization, but remarkably Cdkn1a deletion fully rescued mineralized surface loss. MicroCT shows trends for moderate spaceflight bone loss in WT femurs, and significant losses in the tibia, while Cdkn1a-null femurs showed much larger significant tissue losses, including 25% thinner trabeculae (p < 0.01),40% thinner cortical bone (p < 0.005), and 10% lower percent cortical bone area (p < 0.05). These results indicate that endogenous bone Cdkn1a plays a key role in mechanosensitive downregulation of osteoprecursor proliferation and promotes osteocytic differentiation. In microgravity however, while Cdkn1a deletion rescues mineralization, bone loss quantified by microCT is greatly increased, likely due to the molecular coupling of osteogenesis and osteoclastogenesis. This molecular mechanism opens the possibility for potential pharmacological approaches to mitigate bone loss in space simultaneously targeting Cdkn1a and osteoclast inhibition.

Eduardo A.C. Almeida↗

DOE OSTI2025

Wellbore Stability and Mud Loss Management in Geothermal Drilling: Optimizing Mud Weight to Mitigate Tensile Wellbore Fracturing at The Geysers, California

As part of a U.S. Department of Energy (DOE) Geothermal Technologies Office-funded initiative, Geysers Power Company, LLC, a subsidiary of Calpine Corporation, has been working to enhance drilling performance at the world’s largest geothermal field, The Geysers, in northern California. In a recent drilling operation of the GDC-36 well, excessive mud losses were encountered, initially addressed through repeated but largely ineffective cement plugging. Ultimately, the most effective strategy was to drill blind through the loss zones, made feasible by the high rate of penetration (ROP) achieved with PDC bits, allowing significant progress before the mud tanks were depleted and water-sensitive argillic formation layers could collapse. In response to these challenges, the project team explored alternative methods to minimize downtime and risks associated with cement plugging and continuous mud loss and to contemplate the driving mechanisms for the losses. Wellbore imaging using Formation MicroImager (FMI) and Ultrasonic Borehole Imager (UBI) tools revealed longitudinal tensile fractures, which were attributed to mud weights exceeding the minimum circumferential stress resulting from the native stress field and formation pressure. This study examines the mud losses encountered and leverages wellbore imaging data to understand the mechanisms behind mud induced tensile fracturing in specific rock facies. Understanding fracture behavior across different lithologies is crucial, as fractures within the reservoir can enhance steam migration throughout the system. The reservoir at The Geysers lies within the Mesozoic Franciscan Assemblage, a tectonic mélange formed by subduction. It consists of metamorphosed turbidite sandstone (greywacke) and mudstone (argillite), oceanic upper crust (including greenstone and chert), and serpentinized ultramafic rocks - each exhibiting distinct geomechanical fracturing properties. The structural fabric of the Franciscan Assemblage was shaped by low-angle Mesozoic thrust faulting and later overprinted by sub-vertical strike-slip structures related to the Pacific-North American plate boundary. A wellbore stability model was developed using core measurements and logs to simulate fracturing scenarios during drilling under varying stress conditions. These simulations guided the development of an optimized mud weight management strategy that should enable adaptive adjustments during drilling, reducing the likelihood of tensile fracturing and mud losses, ultimately improving operational efficiency.

15 GEOTHERMAL ENERGY↗

DOE OSTI2026

Quality and Loss Factor Characterization of YBCO Superconducting Transmission Lines for Axion Dark Matter Detection

Axion haloscope experiments aim to detect the conversion of axions into microwave photons under a strong magnetic field through resonant cavity techniques. The conversion produces an extremely small signal, requiring a cryogenic environment to reduce thermal noise, and low-loss superconducting transmission lines for minimal attenuation in the readout chain. Yttrium barium copper oxide (YBCO) cables are a promising candidate. Unlike commonly used low-loss cryogenic cables such as niobium (Nb) and niobium titanium (NbTi), which have low critical fields, YBCO is a high-temperature superconductor that can remain stable in strong magnetic fields. We characterized the quality and loss of five stripline resonators from the Brookhaven Technology Group: three YBCO, a copper reference, and a silver reference. Experimental methodology included collecting scattering parameter data on a vector network analyzer for the samples at 77 K along with room temperature baseline measurements, and employing both Lorentzian-fit and circle-fitting techniques to confirm the coupling regime and corroborate results. We achieved quality factors on the order of $10^3$ with corresponding loss factors on the order of $10^{-1}$ dB/m. Trends were comparable with literature data on Nb and NbTi at 4 K, which did have lower loss under these conditions, but suggested similar or perhaps better loss for YBCO when accounting for the temperature difference. We also developed a cryogenic probe for future measurements in a 14 T applied field at 30 mK. This will serve to directly evaluate YBCO's durability in magnetic fields, and we expect significantly improved performance at millikelvin temperatures.

Marinos, Z. [UCLA]↗

DOE OSTI2021

Levenberg–Marquardt multi-classification using hinge loss function

Incorporating higher-order optimization functions, such as Levenberg-Marquardt (LM) have revealed better generalizable solutions for deep learning problems. However, these higher-order optimization functions suffer from very large processing time and training complexity especially as training datasets become large, such as in multi-view classification problems, where finding global optima is a very costly problem. To solve this issue, we develop a solution for LM-enabled classification with, to the best of knowledge first-time implementation of hinge loss, for multiview classification. Hinge loss allows the neural network to converge faster and perform better than other loss functions such as logistic or square loss rates. Here we prove our method by experimenting with various multiclass classification challenges of varying complexity and training data size. The empirical results show the training time and accuracy rates achieved, highlighting how our method outperforms in all cases, especially when training time is limited. Our paper presents important results in the relationship between optimization and loss functions and how these can impact deep learning problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Loss Analysis and Performance Optimization Pathways of 729-mV Voc Si Solar Cells with Poly-Si on Locally-Etched Dielectric Passivating Contacts

In this article, the loss analysis of silicon solar cells with polysilicon on locally-etched dielectric passivating contacts with Voc=729.0 mV and efficiency=22.6% has been presented. Experimentally, nano-pinholes were introduced in SiO x (2.2 nm) and SiO x /SiN y (2.2 nm/8nm) stack using metal-assisted chemical etching (MACE). SunSolve and Quokka3 were used to simulate the experimental solar cell and investigate the optical and electrical power losses. Simulations suggest maximum power loss occurs due to recombination and resistive losses in the bulk (~0.76 mW/cm2) followed by power loss due to rear contact recombination (~0.35 mW/cm2). Recombination at the front surface also contributes to 0.24 mW/cm2. The effect of improving the bulk lifetime and lowering the recombination current density at the rear side on Voc, FF and hence, efficiency has been investigated. Further, advanced structures have been proposed to minimize recombination and parasitic absorption to achieve higher Voc and Jsc of the solar cells with locally-etched dielectric passivating contacts.

contacts↗

DOE OSTI2021

International collaboration framework for the calculation of performance loss rates: Data quality, benchmarks, and trends (towards a uniform methodology)

Abstract The IEA PVPS Task 13 group, experts who focus on photovoltaic performance, operation, and reliability from several leading R&D centers, universities, and industrial companies, is developing a framework for the calculation of performance loss rates of a large number of commercial and research photovoltaic (PV) power plants and their related weather data coming across various climatic zones. The general steps to calculate the performance loss rate are (i) input data cleaning and grading; (ii) data filtering; (iii) performance metric selection, corrections, and aggregation; and finally, (iv) application of a statistical modeling method to determine the performance loss rate value. In this study, several high‐quality power and irradiance datasets have been shared, and the participants of the study were asked to calculate the performance loss rate of each individual system using their preferred methodologies. The data are used for benchmarking activities and to define capabilities and uncertainties of all the various methods. The combination of data filtering, metrics (performance ratio or power based), and statistical modeling methods are benchmarked in terms of (i) their deviation from the average value and (ii) their uncertainty, standard error, and confidence intervals. It was observed that careful data filtering is an essential foundation for reliable performance loss rate calculations. Furthermore, the selection of the calculation steps filter/metric/statistical method is highly dependent on one another, and the steps should not be assessed individually.

14 SOLAR ENERGY↗

DOE OSTI2022

Testing Low-Loss Microstrip Materials with MKIDs for Microwave Applications

Future measurements of the millimeter-wavelength sky require a low-loss superconducting microstrip, typically made from niobium and silicon-nitride, coupling the antenna to detectors. Here, we propose a simple device for characterizing these low-loss microstrips at 150 GHz. In our device we illuminate an antenna with a thermal source and compare the measured power at 150 GHz transmitted down microstrips of different lengths. The power measurement is made using Microwave Kinetic Inductance Detectors (MKIDs) fabricated directly onto the microstrip dielectric, and comparing the measured response provides a direct measurement of the microstrip loss. Our proposed structure provides a simple device (4 layers and a DRIE etch) for characterizing the dielectric loss of various microstrip materials and substrates. We present initial results using these devices. We demonstrate that the millimeter wavelength loss of microstrip lines, a few tens of millimeters long, can be measured using a practical aluminum MKID with a black body source at a few tens of Kelvin.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Novel artificial neural network model for instantaneous power losses and operational efficiency mapping of MW-scale vanadium redox flow battery for improved technoeconomic analysis

A novel data-driven, machine-learning-based method for modeling the instantaneous power losses of a distribution-sited 2 MW/8MWh vanadium redox flow battery (VRFB), a grid-scale electrochemical storage technology, is introduced and compared against benchmark empirical modeling approaches, including symmetric and asymmetric models, as well as a recent convex hull modeling approach. The novel loss modeling method introduces several advantages over the benchmark models and over simplistic efficiency estimates, the most significant of which is that the model can accurately reflect the stepwise and non-linear parasitic losses associated with the duty cycles of mechanical auxiliary systems like pump motor drives and blower fans. Residuals of the models are compared; the proposed data driven model features significantly improved accuracy over the benchmark models. The model's coefficient of determination is also improved relative to that of the benchmark models. Furthermore, a novel method for visualization of operational efficiency of the grid-scale storage technology is introduced. To demonstrate the benefits of the novel data-driven method for modeling the VRFB, the benchmark models and the proposed models are embedded into an Open DSS distribution network model to study two applications of the grid-scale electrical storage system: load leveling for grid support and energy arbitrage. This article demonstrates that the accuracy of the instantaneous power loss model significantly impacts the understanding of the state of charge of the VRFB. In turn, the accuracy of the efficiency modeling of the VRFB impacts the understanding of the potential economic value and technical benefits to the distribution network operators. In conclusion, the presented power loss modeling approach is, therefore, highly relevant for utility-stakeholders, battery asset owners, system engineers, system designers, and financial planners interested in evaluating or optimizing the operation of grid-scale VRFBs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Electronic energy loss and ion velocity correlation effects in track production in swift-ion-irradiated LiNbO3: A quantitative assessment between structural damage morphology and energy deposition

The primary motivation for studying how irradiation modifies the structures and properties of solid materials involves the understanding of undesirable phenomena, including irradiation-induced degradation of components in nuclear reactors and space exploration, and beneficial applications, including material performance tailoring through ion beam modification and defect engineering. In this work, the formation mechanism of latent tracks with different damage morphologies in LiNbO 3 crystals under 0.09–6.17 MeV/u ion irradiation with an electronic energy loss from 2.6–13.2 keV/nm is analyzed by experimental characterizations and numerical calculations. Irradiation-induced damage is preliminarily evaluated via the prism coupling technique to analyze the correlation between the dark-mode spectra and energy loss profiles of irradiated regions. Under the irradiation conditions of different ion velocities and electronic energy losses, different damage morphologies, from individual spherical defects to discontinuous and continuous tracks, are experimentally characterized. During ion penetration process, the ion velocity determines the spatiotemporal distribution of deposited irradiation energy induced by electronic energy loss, meaning that the two essential factors including electronic energy loss and ion velocity co-affect the track damage. The inelastic thermal spike model is used to numerically calculate the spatiotemporal evolutions of energy deposition and the corresponding atomic temperature under different irradiation conditions, and a quantitative relationship is proposed by comparison with corresponding experimentally observed track damage morphologies. Additionally, the obtained quantitative relationship between irradiation conditions and track damage provides deep insight and guidance for understanding the damage behavior of crystal materials in extreme radiation environments and selecting irradiation parameters, including ion species and energies, for ion beam technique application in atomic-level defect manipulation, material modification, and micro/nanofabrication.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The performance evaluation of direct detection electron energy-loss spectroscopy at 200 kV and 80 kV accelerating voltages

Direct electron detectors (DeDs) have been widely used for imaging studies because of their higher beam sensitivity, lower noise, improved pixel resolution, etc. However, there have been limited studies related to the performance in spectroscopic applications for the direct electron detection. Hereby, taking the advantage of the DeD installed on a high-performance electron energy-loss spectrometer, we systematically studied the performance of a DeD (Gatan's K2 IS) fitted on an aberration-corrected transmission electron microscope (TEM) equipped with an electron monochromator. Using SrTiO3 as the model system, the point spread function in the zero-loss region of the spectrum and the performance for core loss spectroscopy have been investigated under both 200 kV and 80 kV operating conditions. We demonstrate that the K2 detector can achieve an overall better performance at 200 kV than a charge coupled device (CCD) detector. At 80 kV, the K2 DeD is still better than a CCD, except for the relative broad tails of the zero-loss peak. The signal-to-noise ratio is very close for DeD and CCD under 80 kV. Based on our data obtained at different operating voltages, it is clear that DeD will benefit the microscopy community and boost the development of cutting-edge materials science studies by pushing the frontiers in electron energy-loss spectroscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

A large net carbon loss attributed to anthropogenic and natural disturbances in the Amazon Arc of Deforestation

The Amazon forest contains globally important carbon stocks, but in recent years, atmospheric measurements suggest that it has been releasing more carbon than it has absorbed because of deforestation and forest degradation. Accurately attributing the sources of carbon loss to forest degradation and natural disturbances remains a challenge because of the difficulty of classifying disturbances and simultaneously estimating carbon changes. We used a unique, randomized, repeated, very high-resolution airborne laser scanning survey to provide a direct, detailed, and high-resolution partitioning of aboveground carbon gains and losses in the Brazilian Arc of Deforestation. Our analysis revealed that disturbances directly attributed to human activity impacted 4.2% of the survey area while windthrows and other disturbances affected 2.7% and 14.7%, respectively. Extrapolating the lidar-based statistics to the study area (544,300 km 2 ), we found that 24.1, 24.2, and 14.5 Tg C y −1 were lost through clearing, fires, and logging, respectively. The losses due to large windthrows (21.5 Tg C y −1 ) and other disturbances (50.3 Tg C y −1 ) were partially counterbalanced by forest growth (44.1 Tg C y −1 ). Our high-resolution estimates demonstrated a greater loss of carbon through forest degradation than through deforestation and a net loss of carbon of 90.5 ± 16.6 Tg C y −1 for the study region attributable to both anthropogenic and natural processes. This study highlights the role of forest degradation in the carbon balance for this critical region in the Earth system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Effects of collisional ion orbit loss on neoclassical tokamak radial electric fields

We report that ion orbit loss is considered important for generating the radially inward electric field E r in a tokamak edge plasma. In particular, this effect is emphasized in diverted tokamaks with a magnetic X point. In neoclassical equilibria, Coulomb collisions can scatter ions onto loss orbits and generate a radially outward current, which in steady state is balanced by the radially inward current from viscosity. To quantitatively measure this loss-orbit current in an edge pedestal, an ion-orbit-flux diagnostic has been implemented in the axisymmetric version of the gyrokinetic particle-in-cell code XGC. As the first application of this diagnostic, a neoclassical DIII-D H-mode plasma is studied using gyrokinetic ions and adiabatic electrons. The validity of the diagnostic is demonstrated by studying the collisional relaxation of E r in the core. After this demonstration, the loss-orbit current is numerically measured in the edge pedestal in quasisteady state. In this plasma, it is found that the radial electric force on ions from E r approximately balances the ion radial pressure gradient in the edge pedestal, with the radial force from the plasma flow term being a minor component. The effect of orbit loss on E r is found to be only mild.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Effect of resonant magnetic perturbations including toroidal sidebands on magnetic footprints and fast ion losses in HL-2M

Externally applied resonant magnetic perturbations (RMPs), generated by magnetic coils located outside the plasma (referred to as RMP coils), provide an effective way to control the edge localized mode (ELM) in tokamak devices. Due to the discrete nature of the toroidal distribution of these window-frame coils, toroidal sidebands always exist together with the fundamental harmonics designed for ELM control. In this work, the MARS-F code (Liu et al 2000 Phys. Plasmas7 3681) is applied to investigate the detailed features of the RMP spectra considering both the dominant harmonic (n = 2) and the associated sideband (n = 6), and the impact of the combined fields on magnetic footprints as well as on the fast ion losses for a reference double-null scenario in the HL-2M device. It is found that the sum of the n = 2 and n = 6 RMP fields splits the footprint and widens the footprint area, as compared to the single-n (n = 2) harmonic case. The resistive plasma response breaks the up–down symmetry of the footprint pattern on the outer divertor plates, which is otherwise symmetric assuming vacuum RMP fields. Considering fast ion losses, a threshold value exists for the initially launched radial position of test particles, as well as for the RMP coil current, before the loss occurs. When the threshold criterion is satisfied, the combined n = 2 and n = 6 RMP fields enhance the fast ion loss rate by , as compared to that of the n = 2 component alone. These results illustrate the important role of the sideband of RMP fields on the magnetic footprints and fast ion losses in tokamak plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Impact of absorption due to zero-field splitting on loss in dielectrics: A case study in sapphire

The coherence times of superconducting qubits are limited by loss mechanisms, whose microscopic origins have remained elusive. We propose a mechanism caused by transitions between zero-field-split states of paramagnetic impurities or defects. We derive the absorption cross section for a magnetic dipole transition and apply it to calculate the bulk loss tangent. For Cr, Fe, and V impurities in sapphire, we find loss tangents at 4.5 GHz in the range of 10 −9 –10 −8 , comparable to the loss measured in experiments. This value suggests that magnetic loss may be a limiting factor in the coherence times of superconducting qubits.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Entropy-Infused Deep Learning Loss Function for Capturing Extreme Values in Wind Power Forecasting

Extreme scenarios in wind power generation occur with higher frequency and larger magnitude in the recent years due to the ever-increasing extreme meteorological factors. Accurate forecasting of the occurrence of extreme values in wind power generation is of great concern to ensure reliable power system operation. Recently, deep learning models have surged in popularity for wind power forecasting, with the mean squared error (MSE) loss function being commonly used. However, the MSE loss function, being sensitive to extreme values, disproportionately penalizes larger errors, cannot adequately capture the extreme values present in wind energy data, and novel loss functions have seldom been tailored for wind power forecasting. To this end, in this paper, we introduce a novel loss function specifically crafted to capture extreme values in wind power forecasting. The experimental results with four fundamental deep learning methods on open source wind power dataset validate that the new loss function is efficient and superior in all cases compared to MSE in capturing extreme values while maintaining forecasting performance.

17 WIND ENERGY↗

DOE OSTI2021

Extremum Seeking-Based Control System for Particle Accelerator Beam Loss Minimization

Particle accelerators throughout the world vary widely in terms of age and availability of advanced noninvasive diagnostics that provide varying levels of detail about the accelerated beams. Additionally, beam loss measurements and current monitors are ubiquitous in the accelerator community, they are noninvasive, and they are some of the most important metrics in terms of preventing damage or irradiation of beam pipes and equipment for high-energy machines. However, beam loss and current measurements are difficult to use for feedback tuning because of a lack of a known analytic relationship between scalar loss measurements throughout an accelerator and the hundreds of thousands of parameters that influence the beam and time variation of the beam source itself. In this work, we present a model-independent extremum seeking (ES) controller, which has been implemented for automated tuning and optimization of the Los Alamos Neutron Science Center (LANSCE) linear ion accelerator based only on scalar quantities, such as beam loss or flux measurements. We demonstrate the approach on various accelerator subsystems, including groups of radio frequency (RF) accelerating cavities, quadrupole magnets, bending magnets, and steering magnets. This tool is now available as a use graphical user interface (GUI) in the LANSCE control room, allowing beam physicists to choose arbitrary groups of parameters and beam loss or current monitors for adaptive tuning.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Conceptual Design of a Scintillator-Based Fast-Ion Loss Detector for the Wendelstein 7-X Stellarator

Here, a conceptual design of a scintillator-based fast-ion loss detector (FILD) has been developed for the Wendelstein 7-X stellarator (W7-X). Simulations using the Monte Carlo codes ASCOT5 and BEAMS3D have been performed to calculate the expected flux of neutral beam injection (NBI)-generated fast hydrogen ions onto the conceptual detector probe head. These fast-ion loss fluxes have been calculated for several magnetic field configurations as well as probe insertion positions. At the maximum insertion position, both co-and counter-going losses with high incident pitch angles are observed; however, at retracted positions, only co-going fast ions reach the probe head. The FILDSIM code has been used to optimize the geometry of the detector entrance and collimating elements to achieve a wide velocity space coverage as well as a high velocity–space resolution. A synthetic FILD signal is calculated for the expected loss distribution via forward modeling using the instrument response function. The synthetic signal is found to largely retain the velocity space features of the loss distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗