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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multi-device analysis of energy loss duration and pellet penetration with implications for shattered pellet injection in ITER

A robust disruption mitigation system (DMS) requires accurate characterization of key disruption timescales, one of the most notable being the thermal quench (TQ). Recent modeling of shattered pellet injection (SPI) into ITER plasmas, using JOREK and INDEX, suggests long TQ durations (6–10 ms) and slow cold front propagation due to the large plasma size. If validated, these predictions would have an impact on the desired pellet parameters and mitigation strategies for the ITER DMS. To resolve these questions, a database of SPI experiments from several small-to-large sized devices (J-TEXT, KSTAR, AUG, DIII-D, and JET) has been compiled under the auspices of the International Tokamak Physics Activity MHD, disruptions, and control topical group. Analysis of the energy loss duration (proxy for the TQ duration) with machine size is presented for both mixed neon/deuterium (Ne/D) SPI and pure deuterium (D) SPI. Several metrics for the energy loss onset (e.g. soft x-ray signal drop, I p dip, and radiation flash) were considered as the conventional metric, electron cyclotron emission, is often cut-off during SPI. Several scalings with different onset metrics showed an increase in energy loss duration with machine size. The energy loss duration was additionally shown to be a function of the ratio between the number of SPI neon atoms injected and the stored energy. Analysis of the pellet shard position relative to the cold front found that in larger devices, pellets are typically found inboard of the q = 2 surface at the energy loss onset. Lastly, the delay between the pellet shards hitting the q = 2 surface and the energy loss onset was additionally found to increase with machine size. This suggests that the pellet shards in large devices will penetrate faster and further than the cooling front.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

LossLens: Diagnostics for Machine Learning Through Loss Landscape Visual Analytics

Modern machine learning often relies on optimizing a neural network's parameters using a loss function to learn complex features. Beyond training, examining the loss function with respect to a network's parameters (i.e., as a loss landscape) can reveal insights into the architecture and learning process. While the local structure of the loss landscape surrounding an individual solution can be characterized using a variety of approaches, the global structure of a loss landscape, which includes potentially many local minima corresponding to different solutions, remains far more difficult to conceptualize and visualize. To address this difficulty, we introduce LossLens, a visual analytics framework that explores loss landscapes at multiple scales. LossLens integrates metrics from global and local scales into a comprehensive visual representation, enhancing model diagnostics. Here we demonstrate LossLens through two case studies: visualizing how residual connections influence a ResNet-20, and visualizing how physical parameters influence a physics-informed neural network (PINN) solving a simple convection problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Ultra-low loss visible light waveguides for integrated atomic, molecular, and quantum photonics

Atomic, molecular and optical (AMO) visible light systems are the heart of precision applications including quantum, atomic clocks and precision metrology. As these systems scale in terms of number of lasers, wavelengths, and optical components, their reliability, space occupied, and power consumption will push the limits of using traditional laboratory-scale lasers and optics. Visible light photonic integration is critical to advancing AMO based sciences and applications, yet key performance aspects remain to be addressed, most notably waveguide losses and laser phase noise and stability. Additionally, a visible light integrated solution needs to be wafer-scale CMOS compatible and capable of supporting a wide array of photonic components. While the regime of ultra-low loss has been achieved at telecommunication wavelengths, progress at visible wavelengths has been limited. Here, we report the lowest waveguide losses and highest resonator Qs to date in the visible range, to the best of our knowledge. We report waveguide losses at wavelengths associated with strontium transitions in the 461 nm to 802 nm wavelength range, of 0.01 dB/cm to 0.09 dB/cm and associated intrinsic resonator Q of 60 Million to 9.5 Million, a decrease in loss by factors of 6x to 2x and increase in Q by factors of 10x to 1.5x over this visible wavelength range. Additionally, we measure an absorption limited loss and Q of 0.17 dB/m and 340 million at 674 nm. This level of performance is achieved in a wafer-scale foundry compatible Si 3 N 4 platform with a 20 nm thick core and TEOS-PECVD deposited upper cladding oxide, and enables waveguides for different wavelengths to be fabricated on the same wafer with mask-only changes per wavelength. These results represent a significant step forward in waveguide platforms that operate in the visible, opening up a wide range of integrated applications that utilize atoms, ions and molecules including sensing, navigation, metrology and clocks.

Chauhan, Nitesh↗
DOE OSTI2024

Low loss fiber-coupled volumetric interconnects fabricated via direct laser writing

Photonic integrated circuits (PICs) are vital for high-speed data transmission. However, optical routing is limited in PICs composed of only one or a few stacked planes. Further, coupling losses must be low in deployed systems. Previously, we developed the subsurface controllable refractive index via beam exposure (SCRIBE) technique to write accurate 3D gradient refractive index (GRIN) profiles within a mesoporous silica scaffold. Here, we apply SCRIBE to fabricate low loss, broadband, polarization insensitive, fiber-coupled, single-mode volumetric interconnects that include waveguides traversing arbitrary 3D paths. By seamlessly integrating mode-matching subsurface lenses and GRIN waveguide tapers, calibrating for positional writing errors, implementing multipass exposure, automating alignment, and switching to antireflection coated fibers, we reduced the insertion loss for a fiber-PIC-fiber interconnect from 50 to 2.14 dB, or 1.47 dB, excluding the fiber array’s loss. Further, we establish an upper bound of 0.45 dB loss per coupler. We report quality factors of 27,000 and 77,000 and bending losses of 6 and 3 dB/cm for 15 and 30 µm radii microrings, respectively. We also demonstrate Bézier escalators, polarization-rotating and polarization-splitting interconnects, and a seven-channel 25 µm pitch volumetric interconnect. The SCRIBE platform presents a clear path toward realizing 3D PICs with unique functionality.

Optics↗
DOE OSTI2021

Real-Time Edge AI for Distributed Systems (READS): Progress on Beam Loss De-Blending for the Fermilab Main Injector and Recycler

The Fermilab Main Injector enclosure houses two accelerators, the Main Injector and Recycler. During normal operation, high intensity proton beams exist simultaneously in both. The two accelerators share the same beam loss monitors (BLM) and monitoring system. Beam losses in the Main Injector enclosure are monitored for tuning the accelerators and machine protection. Losses are currently attributed to a specific machine based on timing. However, this method alone is insufficient and often inaccurate, resulting in more difficult machine tuning and unnecessary machine downtime. Machine experts can often distinguish the correct source of beam loss. This suggests a machine learning (ML) model may be producible to help de-blend losses between machines. Work is underway as part of the Fermilab Real-time Edge AI for Distributed Systems Project (READS) to develop a ML empowered system that collects streamed BLM data and additional machine readings to infer in real-time, which machine generated beam loss.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Semantic Regression for Disentangling Beam Losses in the Fermilab Main Injector and Recycler

Fermilab’s Main Injector enclosure houses two accelerators: the Main Injector (MI) and the Recycler (RR). In periods of joint operation, when both machines contain high intensity beam, radiative beam losses from MI and RR overlap on the enclosure’s beam loss monitoring (BLM) system, making it difficult to attribute those losses to a single machine. Incorrect diagnoses result in unnecessary downtime that incurs both financial and experimental cost. In this work, we introduce a novel neural approach for automatically disentangling each machine’s contributions to those measured losses. Using a continuous adaptation of the popular UNet architecture in conjunction with a novel data augmentation scheme, our model accurately infers the machine of origin on a per-BLM basis in periods of joint and independent operation. Crucially, by extracting beam loss information at varying receptive fields, the method is capable of learning both local and global machine signatures and producing high quality inferences using only raw BLM loss measurements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Investigating Low Loss Substrates for Improved Qubit Coherence Times

Superconducting qubits are sensitive to dielectric losses from substrates, making the identification, optimization, and preparation of low-loss materials essential for enhancing qubit coherence times. In this work, we utilize Nb superconducting radio-frequency (SRF) cavities as a high-precision measurement tool to study the dielectric loss tangent of substrates with parts-per-billion sensitivity. This technique enables temperature- and field-resolved measurements, providing deep insights into the behavior of candidate materials such as sapphire and silicon. We explore the impact of substrate preparation techniques, examining how surface treatments and cleaning protocols influence dielectric loss. These studies highlight both the microscopic origins of loss in these substrates and the critical role of preparation methods, helping to identify key materials and processes that minimize dielectric loss, crucial for improving qubit performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Air-sea interactions yielding rapid Beaufort Sea ice losses during the 2021 ONR THINICE Pilot Field Campaign

Seasonal sea ice coverage has declined in the Pacific Arctic region. Losses of the ice cover have modified the region’s surface heat and momentum fluxes providing weather systems more direct interaction with the upper ocean. For example, recent cyclones that have passed over these waters have initiated multiple air-sea interactions and have impacted mixed layer depth, wave properties, and sea ice mass budgets due to diabatic and/or advective processes. As a United States Office of Naval Research (ONR) Departmental Research initiative, one key component of the ONR THINICE program was to advance knowledge on Arctic cyclone coupling with the ocean surface, its ice cover, and understand how such coupling can lead to rapid ice loss. Leading up to the primary field campaign in August 2022, a pilot field campaign from 19 August to 13 September 2021 focused in Utqiagvik, Alaska and Longyearbyen, Svalbard was carried out. This period was marked by frequent Arctic cyclones, periods of strong low-level winds, and stints of extreme short-term Beaufort Sea ice area losses. Cyclones traversed these waters much more frequently than usual during this 26-day period, but did not exhibit extreme central pressures indicative of high intensity and impactful storms. Using ERA5 atmospheric reanalysis fields, CERES and AIRS surface flux retrievals, and in situ sensor data collected from ice-tethered profilers and ice mass balance buoys, we highlight air-sea-ice interactions in the Beaufort Sea during and between these cyclones leading up to extreme ice loss events. Our case study analysis is aimed at understanding how Arctic cyclones, including air-sea interactions prompted by their passage over the marginal ice zone, influence the end-of-summer ice conditions and ice loss events. This study provides an example where frequent, yet weak storms drive rather large marginal sea-scale losses albeit with heterogenous sea ice effects at local scales.

Ballinger, Thomas [International Arctic Research C↗
DOE OSTI2026

Estimating Residual Gas Beam Loss in the BNL AGS Booster:Model, Numerical Tools, and Implications for a Polarimeter Chamber

Beamloss from residual gas scattering is calculated for a storage ring of circumference C = 200m, covering a linear magnetic rigidity ramp from B ρ inj = 1.25Tm to B ρ ext = 9.50Tm over tramp = 1.00s. Three loss mechanisms are considered: nuclear inelastic reactions, single Coulomb scattering beyond the acceptance angle of the machine, and charge-state exchange for heavy ions. Calculations are performed for protons and Au 32+ ions, the latter being the charge state delivered by the EBIS pre-injector into the BNL AGS Booster. At a baseline vacuum of P 0 = 5 × 10 −11 mbar the integrated fractional beam loss over the full ramp is negligible for protons (< 0.001%) and 33.1% for Au 32+ . The impact of a 1m polarimeter section at elevated pressure P s = 5 × 10 −9 mbar is evaluated: the proton loss remains negligible, while the Au 32+ loss rises to 45.1%, establishing the vacuum requirement for the polarimeter chamber. In the present compact approximate model, Au 32+ losses are dominated by charge exchange at injection, while proton losses are dominated by single Coulomb scattering. The design, outgassing budget, pumping strategy, and commissioning sequence for a UHV polarimeter chamber housing silicon detectors and ASICs are described in detail.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Machine Protection Studies of Fast Instability-Driven Beam Losses in the EIC Electron Storage Ring

Fast transverse beam instabilities represent one of the most challenging protection scenarios for the Electron-Ion Collider (EIC) electron storage ring (ESR). Coherent betatron oscillations driven by collective effects can grow rapidly and lead to substantial beam losses within only a few tens of turns, posing a threat to collimators, superconducting (SC) magnets, cryogenic systems, and detector components. A dedicated simulation framework based on distributed transverse excitations was developed to evaluate instability-driven beam losses in the ESR. A conservative instability rise time on the order of 10 turns was used to define a bounding protection scenario. Simulations show that the original two-collimator configuration is insufficient to localize losses under all operating conditions, whereas an optimized four-collimator configuration reduces loss leakage into protected regions by more than two orders of magnitude. Nevertheless, the most severe instability scenarios produce catastrophic beam impacts, with nearly half of the stored beam being intercepted by the collimators within a single turn, exceeding the preliminary estimated survivability limits of the baseline collimator design. The results demonstrate that collimation alone is insufficient to guarantee safe ESR operation and must be complemented by a fast machine-protection system. Dedicated turn-by-turn beam-position monitors and fast beam-loss monitors provide sufficient advance warning to detect instability growth and initiate a beam abort before equipment-damaging loss levels are reached. These findings establish quantitative requirements for the ESR machine-protection architecture and support the implementation of a multilayer protection strategy for both accelerator and detector systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Markov Chain Monte Carlo Parameter Estimation of Deflagration Losses in a Rotating Detonation Engine

One of the practical challenges of the studies of rotating detonation engines (RDEs) is the direct estimation of losses from experimental measurements. This study attempts at resolving this limitation by combining a reduced order model (ROM) of the detonation wave characteristics with a Markov chain Monte Carlo parameter estimation framework. The model considers simple deflagration losses and the overall impact of deflagration on RDE performance. To evaluate this model, a Markov Chain Monte Carlo (MCMC) sampling technique was applied to estimate the loss parameters within the model for a set of conditions operated in hydrogen-air over a range of mass flow rates and equivalence ratios. The MCMC parameter estimation framework allowed for the determination of a posterior distribution of the loss parameters for each test condition, an examination of the correlation between the loss parameters and measured performance metrics of the RDE, and an uncertainty propagation of these parameters. The predicted model loss parameters were then compared to indirect experimental measurements of the deflagration combustion fractions to evaluating the validity of the approach, and shed light on the benefits and drawbacks of the model, measurement techniques, and the estimation framework.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

The Budyko shape parameter as a descriptive index for streamflow loss

Increases in evapotranspiration (ET) from global warming are decreasing streamflow in headwater basins worldwide. However, these streamflow losses do not occur uniformly due to complex topography. To better understand the heterogeneity of streamflow loss, we use the Budyko shape parameter (ω) as a diagnostic tool. We fit ω to 37-year of hydrologic simulation output in the Upper Colorado River Basin (UCRB), an important headwater basin in the US. We split the UCRB into two categories: peak watersheds with high elevation and steep slopes, and valley watersheds with lower elevation and gradual slopes. Our results demonstrate a relationship between streamflow loss and ω. The valley watersheds with greater streamflow loss have ω higher than 3.1, while the peak watersheds with less streamflow loss have an average ω of 1.3. This work highlights the use of ω as an indicator of streamflow loss and could be generalized to other headwater basin systems.

large scale analysis↗
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↗