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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Haze Mitigation in High-Resolution Satellite Imagery using Enhanced Style-Transfer Neural Network and Normalization Across Multiple GPUs

Despite recent advances in deep learning approaches, haze mitigation in large satellite images is still a challenging problem. Due to amorphous nature of haze, object detection or image segmentation approaches are not applicable. Also it is practically infeasible to obtain ground truths for training. Bounded memory capacity of GPUs is another constraint that limits the size of image to be processed. In this paper, we propose a style transfer based neural network approach to mitigate haze in a large overhead imagery. The network is trained without paired ground truths; further, perception loss is added to restore vivid colors, enhance contrast and minimize artifacts. The paper also illustrates our use of multiple GPUs in a collective way to produce a single coherent clear image where each GPU dehazes different portions of a large hazy image.

Park, Byung↗
DOE OSTI2020

Designing an Epitaxially-Integrated DBR for Dislocation Mitigation in Monolithic GaAsP/Si Tandem Solar Cells

This work explores epitaxially-integrated distributed Bragg reflectors (DBR) as a strategy to mitigate the impact of threading dislocations on the performance of monolithic GaAs 0.75 P 0.25 /Si tandem solar cells. The constraints present due to materials availability and the optical transmission profile of the GaAs 0.75 P 0.25 top cell require the use of an enhanced bandwidth DBR design achieved by combining two narrow-band DBR’s with different central wavelengths. Here, the impact of this DBR structure on JSC, along with the competing effects of threading dislocation density (TDD), are investigated using a robust, experimentally informed analytical model. Implementing this DBR within the GaAs 0.75 P 0.25 /Si tandem cell structure is predicted to yield a short circuit current enhancement equivalent to an ~1.8× reduction in TDD, providing a clear demonstration of its promise as a design methodology for mitigating the impact of non-negligible defect populations.

14 SOLAR ENERGY↗
DOE OSTI2024

Surf-Deformer: Mitigating Dynamic Defects on Surface Code via Adaptive Deformation

In this paper, we introduce Surf-Deformer, a code deformation framework that seamlessly integrates adaptive defect mitigation functionality into the current surface code workflow. It crafts several basic deformation instructions based on fundamental gauge transformations, which can be combined to explore a larger design space than previous methods. This enables more optimized deformation processes tailored to specific defect situations, restoring the QEC capability of deformed codes more efficiently with minimal qubit resources. Additionally, we design an adaptive code layout that accommodates our defect mitigation strategy while ensuring efficient execution of logical operations. Our evaluation shows that Surf-Deformer outperforms previous methods by significantly reducing the end-to-end failure rate of various quantum programs by 35× to 70×, while requiring only about 50% of the qubit resources compared to the previous method to achieve the same level of failure rate. Ablation studies show that Surf-Deformer surpasses previous defect removal methods in preserving QEC capability and facilitates surface code communication by achieving nearly optimal throughput.

Yin, Keyi↗
DOE OSTI2024

Anomaly Detection and Mitigation for Dynamic Frequency Regulation in Hydropower-Battery Systems

Hydropower operators and energy storage providers are increasingly interested in participating in frequency regulation services, driven by the incentives offered by independent system operators, such as the PJM Interconnection. This transition, however, unfolds against the backdrop of a modernizing and rapidly digitizing power grid, exposing the integrated legacy infrastructure to a multitude of cybersecurity threats. This work presents an approach for developing an anomaly detection and mitigation system to address cybersecurity challenges during the participation of a hydropower-integrated battery energy storage system (BESS) in a frequency regulation market. The applied anomaly detector utilizes machine learning algorithms to provide detailed classification of cyber-physical events. Later, the applied mitigation system triggers predefined corrective actions to minimize the impact of data integrity attacks on the regulation market and system stability. We evaluated the proposed approach on a hydropower-integrated BESS topology, specifically analyzing the slow regulation signal (Reg A) coming from the PJM market. Our simulation results demonstrate that the proposed approach performs well in detecting data integrity attacks within the allocated time frame and also minimizes the system's transient instability during the participation of hydropower and BESS in the regulation market.

battery energy storage system↗
DOE OSTI2023

Adaptive mitigation of time-varying quantum noise

Current quantum computers suffer from non-stationary noise channels with high error rates, which undermines their reliability and reproducibility. We propose a Bayesian inference based adaptive algorithm that can learn and mitigate quantum noise in response to changing channel conditions. Our study emphasizes the need for dynamic inference of critical channel parameters to improve program accuracy. We use the Dirichlet distribution to model the stochasticity of the Pauli channel. This allows us to perform Bayesian inference, which can improve the performance of probabilistic error cancellation (PEC) under time-varying noise. Our work demonstrates the importance of characterizing and mitigating temporal variations in quantum noise, which is crucial for developing more accurate and reliable quantum technologies. Our results demonstrate that Bayesian PEC can outperform non-adaptive approaches by a factor of 4.5x when measured using Hellinger distance from the ideal distribution.

Dasgupta, Samudra↗
DOE OSTI2023

Mitigation of Cosmic Rays-Induced Errors in Superconducting Quantum Processors

Environmental radioactivity and cosmic-rays have recently been identified as a source of decoherence in super-conducting quantum bits (qubits). In particular, the absorption of cosmic-ray muons and gamma rays emitted by naturally occurring radioactive isotopes in the qubit substrate leads to correlated errors in superconducting quantum processors, posing significant challenges to quantum error correction. To enable quantum computing to scale, it is therefore necessary the devel-opment of mitigation strategies to prevent, or keep under control, error bursts due to particle impacts in the chip. While most environmental radioactive sources can be effectively suppressed using dedicated shielding, cosmic-ray muons, with their high penetration capability, can only be mitigated by moving the entire facility in a deep underground laboratory. This work explores the potential for developing a novel class of quantum processors equipped with an active veto system to protect superconducting-based quantum computers from the detrimental effects of atmospheric muons. Such a device would enable the identification of an atmospheric muon interaction within the processor and veto all operations performed during the occurrence of such an interaction. By demonstrating high detection efficiency and negligible dead time, we aim to establish that the future of quantum processors can be envisioned in above-around facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Q-Cluster: Quantum Error Mitigation Through Noise-Aware Unsupervised Learning

Quantum error mitigation (QEM) is critical in reducing the impact of noise in the pre-fault-tolerant era, and is expected to complement error correction in fault-tolerant quantum computing (FTQC). In this work, we propose a novel QEM approach, Q-Cluster, that uses unsupervised learning (clustering) to reshape the measured bit-string distribution. Our approach starts with a simplified bit-flip noise model. It first performs clustering on noisy measurement results, i.e., bit-strings, based on the Hamming distance. The centroid of each cluster is calculated using a qubit-wise majority vote. Next, the noisy distribution is adjusted with the clustering outcomes and the bitflip error rates using Bayesian inference. Our simulation results show that Q-Cluster can mitigate high noise rates (up to 40% per qubit) with the simple bit-flip noise model. However, real quantum computers do not fit such a simple noise model. To address the problem, we (a) apply Pauli twirling to tailor the complex noise channels to Pauli errors, and (b) employ a machine learning model, ExtraTrees regressor, to estimate an effective bit-flip error rate using a feature vector consisting of machine calibration data (gate & measurement error rates), circuit features (number of qubits, numbers of different types of gates, etc.) and the shape of the noisy distribution (entropy). Our experimental results show that our proposed Q-Cluster scheme improves the fidelity by a factor of 1.46x, on average, compared to the unmitigated output distribution, for a set of low-entropy benchmarks on five different IBM quantum machines. Our approach outperforms the state-of-art QEM approaches RZNE [28], M3 [24], Hammer [35], and QBEEP [33] by 1.26x,1.29x,1.47x, and 2.65 x, respectively.

42 ENGINEERING↗
DOE OSTI2023

Forced Power Systems Oscillations Due to Cyberattacks: Threats, Detection and Partial Mitigation

Forced oscillations in power systems can be caused by misconfigured controllers at generator stations. They can also be caused by cyberattacks against the exciters or governors. This paper explores the effects of forced oscillations from cyberattacks on generator excitation and governor systems and the effectiveness of a novel control system for a static var compensator in mitigating those oscillations to enhance transmission system resilience. A brief overview of oscillations, especially forced oscillations, within power systems is presented, along with an overview of cyberattacks on power systems. This paper also examines and implements FACTS devices to partially mitigate the forced oscillations created by cyberattacks by reducing the magnitude of the oscillations caused by the attack. The proposed approach is more effective against attacks targeting exciters.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

DISARM: Target Electronic Device Informed Mitigation of Software Runtime Side-Channel Vulnerabilities

Program runtime/timing attacks exploit variations in a program’s execution times to extract sensitive information from the program (e.g. encryption keys, sensitive variable data, intellectual property). State-of-the-art solutions to runtime side-channel attacks attempt to balance the execution time of the sensitive code for different control flow paths to eliminate the timing leakage. However, during the mitigation process, most techniques do not consider the underlying hardware/device on which the target program is supposed to run on. This can lead to over-fixing (unnecessary extra operations), under-fixing (not solving the imbalance properly), and even failures. Here, we propose DISARM, a joint hardware-software methodology (unlike any existing solution) for mitigating runtime side-channel vulnerabilities that utilizes timing values from real embedded devices to generate targeted software fixes. We implement DISARM to support C/C++/Java source codes and validate it across 22 standard benchmarks. DISARM outperforms state-of-the-art solutions such as PENDULUM and DifFuzzaR in terms of execution time overhead, code size overhead, and correctness on five different embedded/edge devices.

Timing/runtime side-channel↗
DOE OSTI2024

Modifications to the JET Shattered Pellet Injector to Optimize Disruption Mitigation Experiments for Supporting ITER’s DMS Design

Shattered pellet injection (SPI) experiments on Joint European Torus (JET) are an important element in determining the physics basis for mitigating disruptions in ITER. Here, the initial design of the JET SPI system included three barrels to produce pellets with diameters of 4.5, 8.1, and 12.5 mm. The variability of the pellet speed by operating with and without a mechanical punch was limited and led to poor pellet integrity, so the mechanical punch was removed. Fragment size distribution is a function of pellet speed and the desire to change the resulting fragment size distribution was not originally a requirement. After the first set of SPI experiments on JET, different pellet sizes were considered to enable dual injection experiments with identical pellet diameters. It was also determined that speed control is necessary to improve experimental repeatability and to determine how the fragment size distribution impacts mitigation performance. Two barrels were fabricated to form pellets of 10 mm diameter and a third to form an 8.1 mm diameter pellet. New propellant valves were also fabricated and characterized to improve repeatability and overall performance. To have fine control of pellet speed, inserts to reduce the breech volume were fabricated and installed. Laboratory testing was conducted to ensure pellet release and provide a comparison of propellant gas delivered versus pellet speeds for a range of pellet types and mixtures. This article will also discuss how lessons learned from the JET SPI modifications can be applied to other SPI systems, such as the ITER SPI system, as controlling pellet release with the least amount of propellant gas is essential for optimal SPI effectiveness.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Development of an Encoding Method on an Co-simulation Platform for Mitigating the Impact of Unreliable Communication

This report presents a hardware-in-the-loop (HIL) based modeling approach for simulating impacts of unreliable communication on the performance of centralized volt-var control and for developing an encoding method to mitigate the impacts. First, an asynchronous real-time HIL simulation platform is introduced to enable multi-rate co-simulation of a distribution system with many inverter-based distributed energy resources (DERs). The distribution system is modeled by milliseconds phasor-based models and the DERs are modeled by micro-seconds power electronic models. Communication connections between a centralized volt-var controller (modeled externally to the HIL testbed) and smart inverters are built by implementing Modbus links and the Long Term Evolution network. On this co-simulation platform, an enhanced, augmented Lagrangian multiplier based encoded data recovery (EALM-EDR) algorithm for mitigating the impact of unreliable communication is developed and validated. Simulation results demonstrate the efficacy of using the HIL-based co-simulation platform as a power grid digital twin for developing algorithms that coordinate a large number of heterogeneous control systems through wired and wireless communication links.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Real-Time Implementation of Smart Wireless Charging of On-Demand Shuttle Service for Demand Charge Mitigation

This paper presents a smart charge management strategy for an on-demand electric shuttle operating at the National Renewable Energy Laboratory (NREL) campus and supported by an inductive charger at the vehicle's waiting spot. A new control algorithm has been proposed for mitigating the demand charges incurred from the wireless charger. It monitors the shuttle, wireless charger, renewable energy generation, and other loads and regulates charging behavior for demand charge mitigation. Within the control algorithm, an energy prediction is made to estimate the mobility needs of the vehicle and maintain uninterrupted service during operation while still minimizing peak demand. The proposed controller is designed and optimized using a Simulink model for the entire system. It is then implemented and tested in real time at the NREL campus using online cloud services. Two vehicle-use cases' charge-sustaining and charge-depletion operation' are tested under different campus power profiles and drive cycles to assess the controller's performance. In this work, the proposed controller showed a robust performance under different driving scenarios, with high correlation between simulation and experimental data. The results show that proper demand response can be achieved, with an average of 94% reduction of charging loads during peak demand events.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

On the global limits of bioenergy and land use for climate change mitigation

Across energy, agricultural and forestry landscapes, the production of biomass for energy has emerged as a controversial driver of land-use change. We present a novel, simple methodology, to probe the potential global sustainability limits of bioenergy over time for energy provision and climate change mitigation using a complex-systems approach for assessing land-use dynamics. Primary biomass that could provide between 70 EJ year -1 and 360 EJ year -1 , globally, by 2050 was simulated in the context of different land-use futures, food diet patterns and climate change mitigation efforts. Our simulations also show ranges of potential greenhouse gas emissions for agriculture, forestry and other land uses by 2050, including not only above-ground biomass-related emissions, but also from changes in soil carbon, from as high as 24 GtCO 2 eq year-1 to as low as minus 21 GtCO 2 eq year -1 , which would represent a significant source of negative emissions. Based on the modelling simulations, the discussions offer novel insights about bioenergy as part of a broader integrated system. As a result, there are sustainability limits to the scale of bioenergy provision, they are dynamic over time, being responsive to land management options deployed worldwide.

09 BIOMASS FUELS↗
DOE OSTI2024

Tree drought physiology: critical research questions and strategies for mitigating climate change effects on forests

Droughts of increasing severity and frequency are a primary cause of forest mortality associated with climate change. Yet, fundamental knowledge gaps regarding the complex physiology of trees limit the development of more effective management strategies to mitigate drought effects on forests. Here, in this work, we highlight some of the basic research needed to better understand tree drought physiology and how new technologies and interdisciplinary approaches can be used to address them. Our discussion focuses on how trees change wood development to mitigate water stress, hormonal responses to drought, genetic variation underlying adaptive drought phenotypes, how trees ‘remember’ prior stress exposure, and how symbiotic soil microbes affect drought response. Next, we identify opportunities for using research findings to enhance or develop new strategies for managing drought effects on forests, ranging from matching genotypes to environments, to enhancing seedling resilience through nursery treatments, to landscape-scale monitoring and predictions. We conclude with a discussion of the need for co-producing research with land managers and extending research to forests in critical ecological regions beyond the temperate zone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Ray Effect Mitigation Through Reference Frame Rotation

The discrete ordinates method is a popular and versatile technique for solving the radiative transport equation, a major drawback of which is the presence of ray effects. Mitigation of ray effects can yield significantly more accurate results and enhanced numerical stability for combined mode codes. Moreover, when ray effects are present, the solution is seen to be highly dependent upon the relative orientation of the geometry and the global reference frame. It is an undesirable property. A novel ray effect mitigation technique of averaging the computed solution for various reference frame orientations is proposed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Fundamental study on mitigation of rocking motion of a cask system by a gyro system

In Japan, ensuring the structural integrity of cask systems during seismic events is becoming increasingly important. Cask systems, which are free-standing cylindrical structures that contain spent fuel assemblies, are believed to exhibit rocking motions under strong seismic excitations. Thus far, analytical studies conducted by the authors have indicated that cask systems subjected to strong seismic motions, undergo large rocking motions, and, in the worst case, may overturn and collapse. Therefore, reducing the rocking motions of casks to avoid overturning and consequent contamination of radioactive substances is critical. To suppress rocking motions for heavy free-standing structures such as cask systems, we propose a rocking motion suppression system that employs a gyro system. This system is installed in the free-standing structure. A previous analytical study showed that this system largely mitigates rocking motion. In the present study, we fabricated a fundamental cask system model and a gyro system. By using the cask system model without a gyro system, free vibration tests and shaking table tests were conducted to understand the basic characteristics of rocking motion and responses under base excitations. Analyses were also conducted to confirm the validity of the analytical model for rocking motion comparing with the experimental data. Moreover, analyses for the cask system with the gyro system were conducted. From these results, we evaluated the ability of the gyro system to mitigate rocking motion. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Impact of fused silica debris shields and enhanced mitigation techniques on large-aperture beam-sampling optics for the National Ignition Facility

Here, we show that the large-scale routine use of the fused silica debris shield (FSDS) maintains the ∼100× reduction in damage initiation rate and 70% increase in the install lifetime of a new grating debris shield (GDS) observed during pilot operations. Furthermore, we show that the install lifetimes of recycled GDS optics are nearly tripled using additional mitigation strategies such as expanding mitigation processing to include all damage sites larger than 10 μm (LT10) rather than just larger than 50 μm (LT50) and FSDS. We note that there is still a 50% difference between new and recycled optic installation lifetimes. We show that recycled optics have a 3.5× higher apparent initiation rate than new optics when exposed to nominally identical laser conditions.

FSDS↗
DOE OSTI2015

Motion mitigation for lung cancer patients treated with active scanning proton therapy

Purpose: Motion interplay can affect the tumor dose in scanned proton beam therapy. This study assesses the ability of rescanning and gating to mitigate interplay effects during lung treatments. Methods: The treatments of five lung cancer patients [48 Gy(RBE)/4fx] with varying tumor size (21.1–82.3 cm{sup 3}) and motion amplitude (2.9–30.6 mm) were simulated employing 4D Monte Carlo. The authors investigated two spot sizes (σ ∼ 12 and ∼3 mm), three rescanning techniques (layered, volumetric, breath-sampled volumetric) and respiratory gating with a 30% duty cycle. Results: For 4/5 patients, layered rescanning 6/2 times (for the small/large spot size) maintains equivalent uniform dose within the target >98% for a single fraction. Breath sampling the timing of rescanning is ∼2 times more effective than the same number of continuous rescans. Volumetric rescanning is sensitive to synchronization effects, which was observed in 3/5 patients, though not for layered rescanning. For the large spot size, rescanning compared favorably with gating in terms of time requirements, i.e., 2x-rescanning is on average a factor ∼2.6 faster than gating for this scenario. For the small spot size however, 6x-rescanning takes on average 65% longer compared to gating. Rescanning has no effect on normal lung V{sub 20} and mean lung dose (MLD), though it reduces the maximum lung dose by on average 6.9 ± 2.4/16.7 ± 12.2 Gy(RBE) for the large and small spot sizes, respectively. Gating leads to a similar reduction in maximum dose and additionally reduces V{sub 20} and MLD. Breath-sampled rescanning is most successful in reducing the maximum dose to the normal lung. Conclusions: Both rescanning (2–6 times, depending on the beam size) as well as gating was able to mitigate interplay effects in the target for 4/5 patients studied. Layered rescanning is superior to volumetric rescanning, as the latter suffers from synchronization effects in 3/5 patients studied. Gating minimizes the irradiated volume of normal lung more efficiently, while breath-sampled rescanning is superior in reducing maximum doses to organs at risk.

60 APPLIED LIFE SCIENCES↗