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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Conical Magnetic Bearings Developed for Active Stall Control in Gas Turbine Engines

Active stall control is a current research area at the NASA Glenn Research Center that offers a great benefit in specific fuel consumption by allowing the gas turbine to operate beyond the onset of stall. Magnetic bearings are being investigated as a new method to perform active stall control. This enabling global aviation safety technology would result in improved fuel efficiency and decreased carbon dioxide emissions, as well as improve safety and reliability by eliminating oil-related delays and failures of engine components, which account for 40 percent of the commercial aircraft departure delays. Active stall control works by perturbing the flow in front of the compressor stage such that it cancels the pressure wave, which causes the compressor to go into stall. Radial magnetic bearings are able to whirl the shaft so that variations in blade tip leakage would flow upstream causing a perturbation wave that could cancel the rotating stall cell. Axial or thrust magnetic bearings cannot be used to cancel the surge mode in the compressor because they have a very low bandwidth and thus cannot modulate at a high enough frequency. Frequency response is limited because the thrust runner cannot be laminated. To improve the bandwidth of magnetic thrust bearings, researchers must use laminations to suppress the eddy currents. A conical magnetic bearing can be laminated, resulting in increased bandwidth in the axial direction. In addition, this design can produce both radial and thrust force in a single bearing, simplifying the installation. The proposed solution combines the radial and thrust bearing into one design that can be laminated--a conical magnetic bearing. The new conical magnetic bearing test rig, funded by a Glenn fiscal year 2002 Director's Discretionary Fund, was needed because none of the existing rigs has an axial degree of freedom. The rotor bearing configuration will simulate that of the main shaft on a gas turbine engine. One conical magnetic bearing replaces the ball bearing in front of the compressor, and the second replaces the roller bearing behind the burner. The rig was made operational to 10,000 rpm under Smart Efficient Components funding, and both position and current adaptive vibration control have been demonstrated. Upon program completion, recommendations will be made as to the efficacy of the conical magnetic bearing for active stall control.

Trudell, Jeffrey J.↗
NASA NTRS2008

Dependence of Adaptive Cross-correlation Algorithm Performance on the Extended Scene Image Quality

Recently, we reported an adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels between two extended-scene sub-images captured by a Shack-Hartmann wavefront sensor. It determines the positions of all extended-scene image cells relative to a reference cell in the same frame using an FFT-based iterative image-shifting algorithm. It works with both point-source spot images as well as extended scene images. We have demonstrated previously based on some measured images that the ACC algorithm can determine image shifts with as high an accuracy as 0.01 pixel for shifts as large 3 pixels, and yield similar results for both point source spot images and extended scene images. The shift estimate accuracy of the ACC algorithm depends on illumination level, background, and scene content in addition to the amount of the shift between two image cells. In this paper we investigate how the performance of the ACC algorithm depends on the quality and the frequency content of extended scene images captured by a Shack-Hatmann camera. We also compare the performance of the ACC algorithm with those of several other approaches, and introduce a failsafe criterion for the ACC algorithm-based extended scene Shack-Hatmann sensors.

wave-front sensing and control↗
DOE OSTI2019

Dynamic real‐time optimization for a CO 2 capture process

Growing awareness of climate change has led to increased focus on new energy processes that mitigate generation of CO 2 , or provide for its efficient capture. To enable the development of these processes, advanced modeling and optimization platforms have been created. New capabilities among platforms include efficient solution strategies for online optimization problems. For real time, dynamic optimization of CO 2 capture processes, we demonstrate the application of the Python‐based Pyomo platform to facilitate realization of Moving Horizon Estimation and Nonlinear Model Predictive Control, through novel nonlinear optimization and sensitivity strategies. This capability allows large scale, first principle models to be applied for online optimization. Here, we introduce the Control and Adaptation with Predictive Sensitivity Enhancements (CAPRESE) framework to demonstrate this framework for advanced energy processes. Moreover, we present two case studies: profile tracking with detailed tray‐by‐tray distillation models and Bubbling Fluidized Bed reactors for CO 2 capture. © 2018 American Institute of Chemical Engineers AIChE J , 65: e16511 2019

Thierry, David↗
DOE OSTI2025

Adaptive anomaly detection for identifying attacks in cyber-physical systems: A systematic literature review

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods, which focus on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks, with an emphasis on fast data processing and model adaptation. AAD has been researched extensively; however, to the best of our knowledge, our work is the first systematic literature review (SLR) on current research in this field. We present a comprehensive SLR, gathering 397 relevant papers and systematically analyzing 65 of them (47 research and 18 survey papers) on AAD in CPS from 2013 to November 2023. We introduce a novel taxonomy considering attack types, CPS application, learning paradigm, data management, and algorithms. Our findings show that most studies addressed either model adaptation or data processing, but rarely both simultaneously. This indicates a research gap in fully adaptive solutions. We also categorize algorithms, datasets, and attack characteristics, and summarize strengths and weaknesses across the literature. Our review provides a structured and accessible reference for researchers and practitioners, offering insights into key trends and highlighting limitations in current approaches. Finally, we outline several future research directions, including the need for integrated real-time processing and adaptive learning, explainability, and uncertainty quantification in AAD for CPS.

Adaptation↗
DOE OSTI2021

Impact of cyberattacks on safety and stability of connected and automated vehicle platoons under lane changes

Connected and automated vehicles (CAVs) offer a huge potential to improve the operations and safety of transportation systems. However, the use of smart devices and communications in CAVs introduce new risks. CAVs would leverage vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication, thus providing additional system access points compared to traditional systems. Automation makes these systems more vulnerable and increases the consequences of cyberattacks. This study utilizes an infrastructure-based communication platform consisting of cooperative adaptive cruise control and lane control advisories developed by the authors to perform cyber risk assessment of CAVs. The study emulates three types of cyberattacks (message falsification, dedicated denial of service, and spoofing attacks) in a representative traffic environment consisting of multiple CAV platoons and lane change events to analyze the safety and stability impacts of the cyberattacks. Simulation experiments using VISSIM reveals that traffic stream and CAV string is unstable under all three types of cyberattacks. The worst case is represented by the message falsification attack. Increases in volatility are observed over a no attack case, with variations increasing by an average of 43%–51% along with an increase of over 3000 crash conflicts. Similarly, lane change crash conflicts are observed to be more severe compared to rear end crash conflicts, showing a higher probability of severe injuries. Further, the case of slight cyberattack on a single CAV also creates significant disruption in the traffic stream. Analysis of variance (ANOVA) reveals the statistical significance of the results. Furthermore, these results pave the way for future design of secure systems from a monitoring perspective.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Dynamic beam shaping—Improving laser materials processing via feature synchronous energy coupling

Today, tailored laser beams are rarely used and thus an opportunity to optimize existing or introduce new processes is missed. New methods of dynamic beam shaping have the potential to change that in future. This keynote paper deals with methods allowing a transient energy input into the workpiece at such time scales that the underlying interaction processes are guided towards the desired result. It shows principles, categorizes necessary system technology, and gives application examples to familiarize the reader with the topic. It postulates that time-scale-dependent coupling between transient energy input and addressed process features is key for achieving the optimum.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Medium-scale to large-scale implementation of cyber-physical human experiments in live traffic

Autonomous Vehicles (AVs) such as cars and trucks are being developed and tested as Cyber-Physical Human systems while the technology improves. Before these systems can achieve full autonomy, some serve as tools in the form of adaptive cruise control. The CIRCLES Consortium investigates the potential for AVs to increase fuel efficiency of highway traffic by smoothing “stop-and-go” traffic waves that result from normal human driving behavior in congestion. We have performed an experiment to evaluate the real world effects of implementing this strategy. A medium-scale experiment was performed on I-24 near Nashville, TN in August 2021. This was a precursor to a larger experiment that will take place November 2022. We examine how the human part of the experiment will change as we scale up from an 11 vehicle test (four AVs) to 100 AVs. There are many solutions to problems of the medium-scale experiment that would be inconvenient, complicate the experience, or not be practicable. The medium-scale experiment involved 11 cars of which four had a custom control algorithm installed to be engaged by the driver. The large-scale experiment will have 100 cars, all with custom control algorithm installed to act on traffic when the controller is engaged. We examine key choices made for the medium experiment, and how some will be different for the large experiment. Our experience performing the medium-scale experiment has made it clear that repeating our methods from this smaller one are inefficient or impossible if used for the large-scale experiment and will be improved.

McQuade, Sean T.↗
DOE OSTI2019

Describing the users: Understanding adoption of and interest in shared, electrified, and automated transportation in the San Francisco Bay Area

Emerging technologies and services stand poised to transform the transportation system, with large implications for energy use and mobility. The degree and speed of these impacts depend largely on who adopts these innovations and how quickly. Leveraging data from a novel survey of San Francisco Bay Area residents, we analyze adoption patterns for shared mobility, electrified vehicle technologies, and vehicle automation. We find that ride-hailing and adaptive cruise control have penetrated the market more extensively than have electrified vehicles or car-sharing services. Over half of respondents have adopted or expressed interest in adopting all levels of vehicle automation. Overall, there is substantial potential for market growth for the technologies and services we analyzed. Using county fixed effects regressions, we investigate which individual and location-level factors correlate to adoption and interest. We find that, although higher-income people are disproportionately represented among current adopters of most new technologies and services, low- to middle-income people are just as likely to have adopted pooled ride-hailing. Younger generations have high interest in automated and electrified vehicles relative to their current adoption of these technologies, suggesting that young people could contribute substantially to future market growth - as they are doing for ride-hailing. We find no evidence that longer commutes present a barrier to plug-in electric vehicle adoption. Finally, women are less likely than men to adopt and/or be interested in adopting most new transportation technologies, with the exception of ride-hailing; designing or marketing technologies with women's preferences in mind could contribute to future market expansion.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Optimization Stability in Excited-State-Specific Variational Monte Carlo

Here, we investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the choice of minimization algorithm. Using a small cyanine dye molecule as a test case, we systematically perform minimizations using variants of the linear method as both a standalone algorithm and in a hybrid combination with accelerated descent. We demonstrate that adaptive step control is crucial for maintaining the linear method's stability when optimizing complicated wave functions and that the hybrid method enjoys both greater stability and minimization performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Electro-Optical Device with Tunable Transparency Using Colloidal Core/Shell Nanoparticles

Here, suspended particle devices (SPDs) adapted for controlling the transmission of electromagnetic radiation have become an area of considerable focus for smart window technology due to their desirable properties, such as instant and precise light control and cost-effectiveness. Here, we demonstrate a SPD with tunable transparency in the visible regime using colloidal assemblies of nanoparticles. The observed transparency using ZnS/SiO 2 core/shell colloidal nanoparticles is dynamically tunable in response to an external electric field with increased transparency when applied voltage increases. The observed transparency change is attributed to structural ordering of nanoparticle assemblies and thereby modifies the photonic band structures, as confirmed by the finite-difference time-domain simulations of Maxwell’s equations. The transparency of the device can also be manipulated by changing the particle size and the device thickness. In addition to transparency, structural colorations and their dynamic tunability are demonstrated using α-Fe 2 O 3 /SiO 2 core/shell nanomaterials, resulting from the combination of inherent optical properties of α-Fe 2 O 3 /SiO 2 nanomaterials and coloration due to their tunable structural particle assemblies in response to electric stimuli.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Atomic Alignment in PbS Nanocrystal Superlattices with Compact Inorganic Ligands via Reversible Oriented Attachment of Nanocrystals

Nanocrystals (NCs) serve as versatile building blocks for the creation of functional materials with NC self-assembly offering opportunities to enable novel material properties. Here, in this work, we demonstrate that PbS NCs functionalized with strongly negatively charged metal chalcogenide complex (MCC) ligands, such as Sn 2 S 6 4– and AsS 4 3– , can self-assemble into all-inorganic superlattices with both long-range superlattice translational and atomic-lattice orientational order. Structural characterizations reveal that the NCs adopt an unexpected edge-to-edge alignment, and numerical simulation clarifies that orientational order is thermodynamically stabilized by many-body ion correlations originating from the dense electrolyte. Furthermore, we show that the superlattices of Sn 2 S 6 4– -functionalized PbS NCs can be fully disassembled back into the colloidal state, which is highly unusual for orientationally attached superlattices with atomic-lattice alignment. The reversible oriented attachment of NCs, enabling their dynamic assembly and disassembly into effectively single-crystalline superstructures, offers a pathway toward designing reconfigurable materials with adaptive and controllable electronic and optoelectronic properties.

Landau-Ginzburg theory↗
DOE OSTI2022

Dual-energy fast neutron imaging using tunable short-pulse laser-driven sources

Here a novel dual-energy fast neutron imaging technique is presented using short-pulse laser-driven neutron sources to leverage their inherent adaptive spectral control to enable 3D volume segmentation and reconstruction. Laser-accelerated ion beams incident onto secondary targets create directional, broadband, MeV-class neutrons. Synthetic radiographs are produced of multi-material objects using ion and neutron spectra derived from analytic and numerical models. It is demonstrated that neutron images generated from small changes to the neutron spectra, controlled by altering the initial laser conditions, are sufficient to isolate materials with differing attenuation coefficients. This is first demonstrated using a simplistic combinatorial isolation method and then by employing more advanced reconstruction algorithms to reduce artifacts and generate a segmentation volume of the constituent materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

DIII-D research to provide solutions for ITER and fusion energy

The DIII-D tokamak has elucidated crucial physics and developed projectable solutions for ITER and fusion power plants in the key areas of core performance, boundary heat and particle transport, and integrated scenario operation, with closing the core-edge integration knowledge gap being the overarching mission. New experimental validation of high-fidelity, multi-channel, non-linear gyrokinetic turbulent transport models for ITER provides strong confidence it will achieve Q ≥ 10 operation. Experiments identify options for easing H-mode access in hydrogen, and give new insight into the isotopic dependence of transport and confinement. Analysis of 2,1 islands in unoptimized low-torque IBS demonstration discharges suggests their onset time occurs randomly in the constant β phase, most often triggered by non-linear 3-wave coupling, thus identifying an NTM seeding mechanism to avoid. Pure deuterium SPI for disruption mitigation is shown to provide favorable slow cooling, but poor core assimilation, suggesting paths for improved SPI on ITER. At the boundary, measured neutral density and ionization source fluxes are strongly poloidally asymmetric, implying a 2D treatment is needed to model pedestal fuelling. Detailed measurements of pedestal and SOL quantities and impurity charge state radiation in detached divertors has validated edge fluid modelling and new self-consistent 'pedestal-to-divertor' integrated modeling that can be used to optimize reactors. New feedback adaptive ELM control minimizes confinement reduction, and RMP ELM suppression with sustained high core performance was obtained for the first time with the outer strike point in a W-coated, compact and unpumped small-angle slot divertor. Advances have been made in integrated operational scenarios for ITER and power plants. Wide pedestal intrinsically ELM-free QH-modes are produced with more reactor-relevant conditions, Low torque IBS with W-equivalent radiators can exhibit predator-prey oscillations in Te and radiation which need control. High-β P scenarios with q min > 2, q 95 –7.9, β N > 4, β T –3.3% and H 98y2 > 1.5 are sustained with high density ($\overline{n}$ = 7E19 m -3 , f G –1) for 6 τ E , improving confidence in steady-state tokamak reactors. Diverted NT plasmas achieve high core performance with a non-ELMing edge, offering a possible highly attractive core-edge integration solution for reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A multi-model assessment of global freshwater temperature and thermoelectric power supply under climate change

Water temperature is a key abiotic factor influencing aquatic ecosystem health and the services provided to both nature and humans. Global water temperature models offer possibilities to improve our understanding of water temperature regimes, which is increasingly important against the backdrop of climate change. Yet, existing studies have predominantly relied on a single model, which can lead to an incomplete representation of uncertainty and potential biases, in addition to limited insight into the range of possible future conditions, which ultimately reduces the robustness of climate impact assessments. Here, we provide a comprehensive assessment of surface freshwater temperature changes from various river and lake models for both past conditions and under future scenarios of climate change. Global models consistently simulate that surface water temperatures are currently 0.5 °C–0.8 °C higher than at the turn of the century (i.e. 1981–2000), and that warming will extend and intensify with future global change throughout the 21st century. While the strength of warming is highly sensitive to the different water temperature models, emissions scenarios and global climate models, our multi-model ensemble shows a global average annual water temperature rise of between +1.3 °C and +4.1 °C by the end of the century. To illustrate a potential societal impact of our results, we evaluate how future changes in discharge and water temperature may affect existing thermoelectric power plants, estimating average annual reductions of 1.5%–6% in global usable capacity by the end of the century. However, with river water temperatures projected to exhibit more pronounced seasonal patterns in the future—especially under the more extreme climate change scenarios and during summer months in the Northern Hemisphere—intra-annual reductions in usable capacity can be much more severe. Given the challenges associated with (large-scale) adaptation to control water temperature regimes, strong climate change mitigation is crucial for minimising water temperature rises and its associated negative impacts on humankind and ecosystems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Stakeholders’ perceptions towards non-native acacias and implications for their management in Portugal

Abstract Humans act as drivers for the introduction of non-native trees. Some non-native species may become invasive and cause undesirable impacts, thereby motivating targeted decision-making and management actions. Australian acacias (or wattles; genus Acacia subgenus Phyllodineae) have been introduced worldwide, offering both opportunities and risks for local communities. Understanding how stakeholders perceive invasive acacias is paramount to assist effective decision-making. We assessed stakeholders’ perceptions about these non-native acacias, their invasion process, social-ecological impacts and management. We conducted a questionnaire-based survey with experienced managers and decision-makers in Northern Portugal, where acacia invasions are widespread. We found that most stakeholders are not able to recognize non-native species, failing to identify the introduction period, drivers of dispersion and appropriate management methods of Australian acacias. We could also identify different stakeholder perceptions on the benefits and negative impacts provided by these species. We call for the implementation of technical training and information outreach strategies to address stakeholders’ lack of knowledge (and experience) on the recognition and identification of non-native trees, as well as on their introduction and invasion history, drivers of dispersion, costs and benefits, and effective management actions. Stakeholders’ engagement should be promoted in the design and implementation of biosecurity efforts to control (and/or adapt to) invasive acacias at relevant scales of invasion management.

Vaz, Ana Sofia↗
DOE OSTI2022

Evaluating Efficiency and Security of Connected and Autonomous Vehicle Applications

Evaluating efficiency and security of Connected and Autonomous Vehicles (CAVs) requires an environment that can support applications and measurements under real-world conditions. This work introduces our implementation and evaluation of a Connected and Autonomous Vehicle Research Environment (CAVRE). We implement and evaluate an existing CAV application called Cooperative Adaptive Cruise Control (CACC) using physical Vehicle-to-Vehicle (V2V) communications between a virtual agent and a real autonomous vehicle operating on a steerable dynamometer. CAVRE allows the follower to autonomously control longitudinal behavior on the dynamometer in order to maintain a steady following time gap from the leader. The effects of a wireless jamming attack on CACC and fuel efficiency is also evaluated. By executing attacks in a controlled environment, we learn how compromised communications can degrade CAV applications. We show that jamming V2V communications can impact CACC’s string stability and decrease fuel efficiency by more than 50%.

Taylor, Curtis↗
DOE OSTI2020

Resonance Suppression based on Predictive Control of Grid-following Inverters with LCL Filter in Weak Grid Condition

This paper presents an effective resonance suppression control when grid interactive inverter with LCL filter experience weak grid conditions. The resonance suppression mechanism is based on finite-set model predictive control (FSMPC) with adaptive cost function to alter the controller objectives seamlessly. The large parasitic impedance and low short circuit ratio (SCR) of weak grid challenges the operation of gridconnected inverters. Specifically, the LCL filter resonance may get excited, resulting in collapse of the inverter operation. To address this issue, an effective active damping approach is implemented in the proposed control. In the proposed active damping scheme for resonance suppression, the feedback currents are switched based on the operating conditions of inverter. During the stiff grid conditions, grid current serves as feedback to the controller. While in the weak grid conditions, the inverter current is selected as feedback signal. The toggling action between these two feedback currents is determined by comparing moving RMS of grid current with threshold current as constraint in the cost function of the proposed MPC scheme. The threshold current for toggling action is based on the reference active and reactive power setpoints plus an acceptable band of variation. The theoretical analysis is verified by several case studies.

Umar, Muhammad Farooq↗