Search NASA⌕ Search

SEARCH · Search NASA

Results for “EPFL”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Boundary, SOL, and Divertor Physics Studies on TCV (Final Report for Research Funded by DoE Award DE-SC0020327)

Research supported under this grant was organized around two diagnostic systems installed on the TCV tokamak located at EPFL in Lausanne, Switzerland: Multi-Spectral Imaging (MSI) and Gas-Puff Imaging (GPI). MSI monitors 2-d time-history images of up to 10 spectral lines, in the visible, using identical views for all wavelengths. The primary application of MSI is to infer 2-d time histories of electron temperature and density in the Scrape-Off-Layer (SOL) of diverted plasmas, utilizing ratios of emission from multiple neutral helium lines. The atomic models are validated against 1-d Thomson scattering measurements. SOL density and temperature maps are analyzed to infer divertor dynamics, including particle and power flows, for a variety of divertor configurations, and specifically as flux expansion along the long-legged outboard divertor is systematically varied. GPI is used to measure details of edge fluctuations in the SOL, particularly as a function of plasma triangularity (δ), including both positive and negative δ. A threshold is found, whereby for δ<-0.3, edge turbulence in the far SOL is completely suppressed. Dynamics of the filamentary turbulence was also analyzed using advance machine learning techniques. Research in support of four PhD theses was carried out within the scope of this Award, including 2 at MIT and 2 at EPFL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Novel Data Driven Noise Emulation Framework using Deep Neural Network for Generating Synthetic PMU Measurements

Sensors play a critical role in supporting day-to-day grid operations and they are essential to operator’s decision-making process. Furthermore, sensors and sensor behaviors need to be emulated with grid simulations to perform modeling studies and to design cutting edge power systems applications. Ensuring the accurate behavior of these applications requires accurate emulation of sensors and pertinent signals. However, most grid simulators and modeling tools assume either zero error scenarios or simplistic noise models that may not always correlate to real-world sensors. To address the above issue, this work presents an initial study on the noise characteristics of phasor measurement units (PMUs), along with models for recreating their unique noise signatures. The proposed methods (both analytical and machine-learning-based) provide a substantial increase in a sensor’s model fidelity, a feature that can be leveraged by an end-user application to yield more accurate system representations. The proposed methods were then applied to micro PMU data from the EPFL microgrid campus to extract sensor noise profiles. This data was used to train a deep learning model, which was tested to emulate the noise characteristics present in actual signals. Based on the observed results and the employed data-driven methodology, the proposed methods may be adapted to replicate the behavior of other grid sensors and power new applications capable of detecting sensor degradation and eventual device failures in near real-time.

PMU, noise emulation, synthetic measurements, deep↗
DOE OSTI2024

PEC Performance Measures from Literature Reports

This dataset is a capture of PEC experimental performance metrics data aggregated from publications and included here in the measurement and format provided by the authors. The measurements captured are based on rate of hydrogen production by PEC devices under illumination. Original creator of this dataset: Wen-Hui (Sophia) Cheng (National Cheng Kung University) Contributors to this dataset: Joel Ager (LBNL), H. Nishiyama et al. (Meiji University), I. Holmes-Gentle (EPFL), Yanfa Yan (University of Toledo), Aditya Mohite (Rice University), Zetian Mi (University of Michigan).

08 HYDROGEN↗
DOE OSTI2026

DEMO-FTES: Development, Monitoring, and Control of Fracture Thermal Energy Storage in Crystalline Rock Formations (CRADA Final Report)

The DEMO-FTES project investigated the feasibility of Fracture Thermal Energy Storage (FTES) as a seasonal energy storage solution in crystalline rock formations. FTES leverages hydraulically induced fractures to exchange heat between circulating fluids and the surrounding rock mass, enabling long-term thermal energy retention due to the high specific heat and low thermal conductivity of rock. This approach has the potential to reduce heating and cooling energy demands and enhance building energy resilience. The project combined dimensional analysis, numerical modeling, laboratory experiments, and meso-scale field tests to evaluate FTES performance and advance its technology readiness level from 3 to 5. Scaling analysis identified key dimensionless parameters governing heat transfer and fluid flow, ensuring laboratory and field tests were representative of larger-scale systems. Numerical simulations using TOUGH and iTOUGH2 frameworks supported experiment design and interpretation, modeling fracture geometry, thermal-hydraulic behavior, and thermo-mechanical coupling. Laboratory tests at EPFL involved creating single and multiple fractures in 25 cm cubic samples of Gabbro and Granite under true triaxial stress.

25 ENERGY STORAGE↗
DOE OSTI2026

Unsupervised Detection of SOC Spoofing in OCPP 2.0.1 EV Charging Communication Protocol Using One-Class SVM

The electric vehicles (EVs) market keeps growing globally; thus, it is critical to secure the EV charging communication protocols in order to guarantee reliable and fair charging operations among the customers. The Open Charge Point Protocol (OCPP) 2.0.1 supports the communication between the Electric Vehicle Supply Equipment (EVSE) and Charging Station Management Systems (CSMSs); therefore, it becomes vulnerable to several types of attacks, which aim to jeopardize smart charging, billing, and energy management. Specifically, OCPP 2.0.1 allows the self-reporting of the State of Charge (SOC) values, which makes it vulnerable to spoofing-based cyberattacks, which target manipulating the scheduling priorities, distorting the load forecasts, and extending the charging sessions in an unfair manner. In this paper, we try to address this type of attack by providing a comprehensive analysis of the SOC spoofing attacks and introducing a novel unsupervised detection framework based on the One-Class Support Vector Machine (OCSVM) algorithm. Specifically, two types of attack scenarios are analyzed (i.e., priority manipulation and session extension) by deriving engineered features that capture the nonlinear relationships under normal charging behavior. Detailed simulation-based results are derived by utilizing the DESL-EPFL Level 3 EV charging dataset. Our results demonstrate high F1-score and recall in identifying spoofed SOC values and that the proposed OCSVM model demonstrates superior performance compared to alternative clustering and deep-learning based detectors.

EV charging↗
DOE OSTI2024

Gamma-ray Spectroscopy in Low-Power Nuclear Research Reactors

Gamma-ray spectroscopy is an effective technique for radioactive material characterization, routine inventory verification, nuclear safeguards, health physics, and source search scenarios. Gamma-ray spectrometers typically cannot be operated in the immediate vicinity of nuclear reactors due to their high flux fields and their resulting inability to resolve individual pulses. Low-power reactor facilities offer the possibility to study reactor gamma-ray fields, a domain of experiments hitherto poorly explored. In this work, we present gamma-ray spectroscopy experiments performed with various detectors in two reactors: The EPFL zero-power research reactor CROCUS, and the neutron beam facility at the Ohio State University Research Reactor (OSURR). We employed inorganic scintillators (CeBr3), organic scintillators (trans-stilbene and organic glass), and high-purity germanium semiconductors (HPGe) to cover a range of typical—and new—instruments used in gamma-ray spectroscopy. The aim of this study is to provide a guideline for reactor users regarding detector performance, observed responses, and therefore available information in the reactor photon fields up to 2 MeV. The results indicate several future prospects, such as the online (at criticality) monitoring of fission products (like Xe, I, and La), dual-particle sensitive experiments, and code validation opportunities.

Pakari, Oskari V. (ORCID:0000000337048190)↗
DOE OSTI2022

Development of a high fidelity model of the CROCUS experimental reactor

Measurements of scalar flux distributions with fine spatial and energy resolutions are needed to remedy one of the validation shortcomings of the novel neutronics full core solvers, such as MPACT and nTRACER. While a very detailed resolution of the flux can be calculated with such codes, only a limited experimental data set is available to check their accuracy. Such type of measurements are on-going at the zero power reactor CROCUS, operated at the Laboratory for Reactor Physics and System Behaviours of the EPFL, thanks to the development of advanced miniature neutron detection systems. This kind of experimental data would provide the community with a suitable benchmark for the validation of high fidelity neutronics solvers. In parallel, a multi-physics solver for steady-state and transient analysis of nuclear reactors, named GeN-Foam, has been developed. Based on the finite-volume OpenFOAM library, GeN-Foam provides us with enough flexibility to analyze non-conventional reactor geometries such as that of CROCUS. While CROCUS heterogeneities cannot be modeled by MPACT and nTRACER for the moment, GeN-Foam offers a unique opportunity to build a high fidelity model which mimics these codes' method to reach sub-pin simulation resolution. This document aims at describing the work achieved to get from the existing GeN-Foam model of the CROCUS reactor based on a structured mesh and using the neutron diffusion, the first high-fidelity model using discrete ordinates method as an approximation to neutron transport and an unstructured mesh for inter lattice water gap description and sub-pin heterogeneous modeling. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

The role of local shipping emissions in aerosol-cloud interactions in the central Arctic

Arctic shipping is projected to increase as sea ice retreats, yet the impact of modern low-sulfur ship emissions on Arctic clouds and radiation remain poorly constrained. We use year-long in situ observations from the MOSAiC expedition to characterize ship-aerosol-cloud interactions for an icebreaker burning ultra-low sulfur fuel (0.1% mass per mass). Exhaust plumes were found to be strongly enriched in Aitken-mode particles, organic aerosol, and black carbon, but showed no detectable enhancement in particulate sulfate. Despite reduced hygroscopicity relative to ambient aerosols, ship emissions substantially increased local cloud condensation nuclei concentrations. A droplet activation parameterization was applied to quantify responses in cloud droplet number concentration ( N d ) to ship-induced perturbations in low-level Arctic clouds. In winter, abundant background accumulation-mode particles from Arctic haze supplied nearly all cloud droplets, while additional particles from ship emissions had little impact on N d . In contrast, during summer months, when unperturbed background aerosol concentrations are low, ship emissions nearly doubled N d compared to average background conditions and increased N d by a factor of five compared to very clean background conditions (25th percentile of background aerosol number concentrations). Longwave radiative transfer simulations for typical conditions of summer Arctic low-level clouds/fog suggest that these ship-induced increases in N d locally (i.e. <100 km downwind) lead to enhanced net surface longwave fluxes and consequent warming, primarily for optically thin clouds (liquid water path (LWP) ⩽ 30 g·m −2 ). For LWP = 10 g · m −2 , ship emissions lead to an increase of 1 W · m −2 in cloud longwave forcing at the surface compared to average unperturbed conditions (+7% relative increase), and up to 4 W · m −2 when compared to very clean background conditions (+22% relative increase). Even ultra-low sulfur fuel emissions can therefore locally and episodically modify Arctic cloud microphysics and radiative properties, especially during summer, implying that future increases in Arctic shipping could have non-negligible regional climate impacts.

Arctic↗
DOE OSTI2025

Learning plasma dynamics and robust rampdown trajectories with predict-first experiments at TCV

The rampdown phase of a tokamak pulse is difficult to simulate and often exacerbates multiple plasma instabilities. To reduce the risk of disrupting operations, we leverage advances in Scientific Machine Learning (SciML) to combine physics with data-driven models, developing a neural state-space model (NSSM) that predicts plasma dynamics during Tokamak à Configuration Variable (TCV) rampdowns. The NSSM efficiently learns dynamics from a modest dataset of 311 pulses with only five pulses in a reactor-relevant high-performance regime. The NSSM is parallelized across uncertainties, and reinforcement learning (RL) is applied to design trajectories that avoid instability limits. High-performance experiments at TCV show statistically significant improvements in relevant metrics. A predict-first experiment, increasing plasma current by 20% from baseline, demonstrates the NSSM’s ability to make small extrapolations. The developed approach paves the way for designing tokamak controls with robustness to considerable uncertainty and demonstrates the relevance of SciML for fusion experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Sources and Composition of Organic Aerosols in the Central Arctic during Spring and Summer

Organic aerosols (OA) are a major component of Arctic aerosol mass and influence the region’s radiation budget, yet their sources and physicochemical properties remain largely unknown. We investigate OA sources and climate-relevant characteristics over the central Arctic Ocean in spring and summer, by applying positive matrix factorization to aerosol mass spectrometry data from two ship-based expeditions (2018 and 2020), complemented by total and interstitial aerosol measurements during fog periods. Six distinct OA factors were identified: haze-related OA, Arctic oxygenated OA, two mixed-OA types resembling biomass burning and primary marine OA linked to warm-air intrusions, marine OA, and hydrocarbon-related OA. Seasonal transitions strongly shaped OA composition. Following polar sunrise, highly oxygenated OA, likely formed secondarily from photo-oxidized volatile organic compounds, became dominant. After the polar vortex collapsed in May, episodic spikes in marine OA from the marginal ice zone appeared, alongside a reduced influence from Eurasian anthropogenic sources. These transitions influenced OA oxidation state and related properties including volatility, acidity, and hygroscopicity, highlighting the role of the Arctic spring atmosphere as an active photochemical reactor. Overall, OA was highly oxidized, with particles activated in fog during summer showing even greater oxidation, suggesting that central Arctic OA can be highly cloud active.

Arctic haze↗
DOE OSTI2026

Results from the last DD and DT JET campaigns in the framework of the EUROfusion Tokamak Exploitation Work Package activity

JET, the only tokamak capable of operating with deuterium–tritium (D–T) fuel (since TFTR was shutdown in 1999), has provided essential experimental data to support ITER and DEMO design and operation. Within the EUROfusion Tokamak Exploitation Work Package, JET completed its final campaigns (2022–2023), culminating in the third D–T campaign (DTE3). These experiments addressed key challenges in plasma scenarios, exhaust control, and tritium management under reactor-relevant conditions. Significant progress was achieved in demonstrating ITER-like integrated scenarios with impurity seeding, achieving partial divertor detachment and high confinement ($H_{98}(y,2)$ ≈ 0.85) at 3 MA in D–T plasmas. Advanced exhaust regimes such as quasi-continuous exhaust (QCE) and X-point radiator (XPR) were successfully achieved first in D–D and then extended to D–T operation, confirming their relevance for mixed isotope operation. Operational milestones included a new world record of 69 MJ fusion energy in tritium-rich hybrid plasmas and long-pulse H-mode operation up to 60 s, contributing with unique data to the CICLOP database. Physics studies focused on peeling-limited pedestals in support of ITER and improved understanding of edge stability and impurity screening in metallic environments. Extensive usage of the shattered pellet injector (SPI) on JET provided critical information for the design of the ITER disruption mitigation system (DMS). Real-time control systems for D/T ratio control and plasma exhaust were deployed and demonstrated in D–D and D–T, while energetic particle physics investigations unfolded the role of fast ions in turbulence suppression mechanisms. Comprehensive tritium retention studies using gas balance method, post-mortem analysis, and ITER-relevant laser induced desorption spectroscopy (LIDS) diagnostics provided essential input for tritium accountancy strategies. These results are validating the ITER operational concepts, inform DEMO design, and deliver critical experience in nuclear operation and scenario integration.

disruptions↗
DOE OSTI2025

Characteristics and effects of aerosols during blowing snow events in the central Arctic

Sea salt aerosol (SSaer) significantly impacts aerosol-radiation and aerosol-cloud interactions, and sublimated blowing snow is hypothesized to be an important SSaer source in polar regions. Understanding blowing snow and other wind-sourced aerosols’ climate relevant properties is needed, especially during winter when Arctic amplification is greatest. However, most of our understanding of blowing snow SSaer comes from modeling studies, and direct observations are sparse. Additionally, SSaer can originate from multiple sources, making it difficult to disentangle emission processes. Here, we present comprehensive observations of wind-sourced aerosol during blowing snow events from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic. High wind speed strongly enhances total aerosol number, submicron sodium chloride mass, cloud condensation nuclei concentrations, and scattering coefficients. Generally, the relative response of aerosol properties to wind speed enhancement is strongest in fall when Arctic aerosol concentrations are lowest. Blowing snow events showed similar aerosol and environmental properties across events, apart from occasions with high snow age (>6 days since last snowfall). Coarse-mode number concentrations (>1 μm) are better explained by variability in wind speed averaged over 12-h air mass back trajectories arriving at the MOSAiC site compared to local, instantaneous wind speed, suggesting the importance of regional transport and consideration of air mass history for wind-driven aerosol production. These MOSAiC observations provide new insights into wind-driven aerosol in the central Arctic and may help validate modeling studies and improve model parameterizations particularly for aerosol direct and indirect radiative forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Node Distortions as a Means of Defect Engineering in Zr-Based MOFs

Defect engineering in Zr-based metal–organic frameworks (Zr-MOFs) has focused primarily on missing-linker defects. However, recent studies suggest that node dehydroxylation–which creates distortions and coordinatively unsaturated Zr sites (Zr cus )–may have a more significant impact on properties. The present work uses pair distribution function (PDF) and thermogravimetric analysis coupled with systematic defect manipulation to study the effect of node dehydroxylation and missing-linker defects in UiO-66. By employing rapid heat treatment (RHT) under humid flow, we tracked the transition from high-symmetry [Zr 6 O 4 (OH) 4 ] 12+ to distorted [Zr 6 O 6 ] 12+ nodes. This structural evolution significantly improves As(V) uptake, whereas increasing the number of missing linkers–via chemical treatment or RHT of mixed-ligand frameworks–fails to enhance performance. Crucially, our detection of distorted nodes in as-synthesized UiO-66 also raises the possibility that these defects were silently present in many earlier studies that span various applications, where their role in governing performance may have been inadvertently overlooked. The present study challenges the prevailing “missing-linker” paradigm and establishes cluster dehydroxylation as a defect-engineering strategy to enhance Lewis-acidic performance in Zr-MOFs.

Adsorption↗
DOE OSTI2024

Measurement of the effective leptonic weak mixing angle

Using pp collision data at $\sqrt{s}$ = 13 TeV, recorded by the LHCb experiment between 2016 and 2018 and corresponding to an integrated luminosity of 5.4 fb −1 , the forward-backward asymmetry in the pp → Z/γ* → μ + μ − process is measured. The measurement is carried out in ten intervals of the difference between the muon pseudorapidities, within a fiducial region covering dimuon masses between 66 and 116 GeV, muon pseudorapidities between 2.0 and 4.5 and muon transverse momenta above 20 GeV. These forward-backward asymmetries are compared with predictions, at next-to-leading order in the strong and electroweak couplings. The measured effective leptonic weak mixing angle is ${\sin}^2{\theta}_{\textrm{eff}}^{\ell }=0.23147\pm 0.00044\pm 0.00005\pm 0.00023,$ where the first uncertainty is statistical, the second arises from systematic uncertainties associated with the asymmetry measurement, and the third arises from uncertainties in the fit model used to extract ${\sin}^2{\theta}_{\textrm{eff}}^{\ell }$ from the asymmetry measurement. This result is based on an arithmetic average of results using the CT18, MSHT20, and NNPDF31 parameterisations of the proton internal structure, and is consistent with previous measurements and with predictions from the global electroweak fit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Smart building HVAC control challenge: experience and solutions from the ADRENALIN project

A smart building HVAC control competition crowdsourced and compared algorithms on fair and equal ground using the standardized BOPTEST framework. The competition attracted 138 participants, but only 9% submitted valid solutions for the final stage, highlighting the complexity of advanced HVAC control design. The winning solutions showed significant potential to reduce energy use and cost by shifting demand, without compromising occupant comfort. Across scenarios, thermal energy cost reductions of 36–76% relative to a baseline, were achieved. In peak heat periods, the cost reduction leveraged limited energy use reduction (0–15%), but more significant energy price reduction (34–62%). This shows smart controls' ability to avoid as much as possible consumption during the morning peak hours, when spot prices are tendentially the highest. Hosting the competition has highlighted challenges in creating competitions that both are fair and promotes solutions that are transferable to real life implementation.

BOPTEST↗
DOE OSTI2024

Direct prediction of saturated neoclassical tearing modes in slab using an equilibrium approach

We demonstrate for the first time that the nonlinear saturation of neoclassical tearing modes (NTMs) can be found directly using a variational principle based on Taylor relaxation, without needing to simulate the intermediate, resistivity-dependent dynamics. As in previous investigations of classical tearing mode saturation (Loizu et al 2020 Phys. Plasmas 27 070701; Loizu and Bonfiglio 2023 J. Plasma Phys. 89 905890507), we make use of Stepped Pressure Equilibrium Code (SPEC) (Hudson et al 2012 Phys. Plasmas 19 112502), an equilibrium solver based on the variational principle of the multi-region relaxed magnetohydrodynamics (MHDs), featuring stepped pressure profiles and arbitrary magnetic topology. We work in slab geometry and employ a simple bootstrap current model J bs = C$\boldsymbol{\nabla}$p to study the bootstrap-driven tearing modes, scanning over the asymptotic matching parameter Δ' and bootstrap current strength. Saturated island widths produced by SPEC agree well with the predictions of an initial value resistive MHDs code (Huang and Bhattacharjee 2016 Astrophys. J. 818 20) while being orders of magnitude faster to calculate. Additionally, we observe good agreement with a simple analytical modified Rutherford equation, without requiring any fitting coefficients. The match is obtained for both linearly unstable classical tearing modes in the presence of bootstrap current, and NTMs, which are linearly stable but nonlinear-unstable due to the effects of the bootstrap current.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Advances in 3D transient plasma dynamics and control through MHD and hybrid fluid-kinetic simulations with JOREK

Transient phenomena and their control are of high relevance in magnetic confinement fusion plasmas to guarantee a stable and safe plasma operation. Interpretative simulations can maximize the insights gained from experiments on present machines and predictive simulations can help in the preparation of design, mitigation techniques and operational scenarios for future devices. In this article, we provide an overview of recent advances and novel scientific results obtained with the 3D non-linear hybrid fluid-kinetic code JOREK, covering physics of plasma transients from the core to the scrape-off layer (SOL) both for tokamak and stellarator devices. Substantial progress was made in the physics understanding, model validation with experiments and experiment interpretation, thus, giving confidence for predictions to devices like DTT, ITER and DEMO. The topics addressed comprise a wide range: the edge physics of new operation scenarios and edge localized mode suppression; major disruptions with a focus on runaway electrons and vertical displacement events as well as disruption mitigation by shattered pellet injection; the physics mechanisms and operational limits of the flux pumping regime for sawtooth control; MHD limits of stellarators and work towards incorporating advanced edge/SOL/exhaust dynamics; continuing improvements of the code for more efficient hybrid simulations on conventional and accelerated high performance computing architectures.

disruptions↗