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DOE OSTI2023

The Impact of Operated Window Shading on Visual Comfort, Non-Visual Health, and Energy Demand from Electric Lighting

This paper introduces a simulation-based workflow to assess annual circadian lighting performance, glare risk and energy demand for an array of seated view positions under operated shading and electric lighting conditions. This workflow uses a combination of 9-band and 81-band simulations to represent daylight and electric lighting respectively. Annual daylight-driven calculations rely on a python-based code provided in the LARK simulation engine which was used to run 180-degree high dynamic range (HDR) renderings with 9-bands of spectral resolution. The results reveal the impact of shading systems on equivalent melanopic lux (EML) and daylight glare probability (DGP) over time and the energy demand (kWh) from electric lighting systems to supplement eye-level recommendations from the WELL v2 Building Standard.

Rockcastle, Siobhan↗

NASA NTRS1991

Nonlinear static and dynamic finite element analysis of an eccentrically loaded graphite-epoxy beam

The Dynamic Crash Analysis of Structures (DYCAT) and NIKE3D nonlinear finite element codes were used to model the static and implulsive response of an eccentrically loaded graphite-epoxy beam. A 48-ply unidirectional composite beam was tested under an eccentric axial compressive load until failure. This loading configuration was chosen to highlight the capabilities of two finite element codes for modeling a highly nonlinear, large deflection structural problem which has an exact solution. These codes are currently used to perform dynamic analyses of aircraft structures under impact loads to study crashworthiness and energy absorbing capabilities. Both beam and plate element models were developed to compare with the experimental data using the DYCAST and NIKE3D codes.

Fasanella, Edwin L.↗

DOE OSTI2022

Uncovering the hydride ion diffusion pathway in barium hydride via neutron spectroscopy

Solid state materials possessing the ability for fast ionic diffusion of hydrogen have immense appeal for a wide range of energy-related applications. Ionic hydrogen transport research is dominated by proton conductors, but recently a few examples of hydride ion conductors have been observed as well. Barium hydride, BaH 2 , undergoes a structural phase transition around 775 K that leads to an order of magnitude increase in the ionic conductivity. This material provides a prototypical system to understand hydride ion diffusion and how the altered structure produced by the phase transition can have an enormous impact on the diffusion. We employ quasielastic and inelastic neutron scattering to probe the atomic scale diffusion mechanism and vibrational dynamics of hydride ions in both the low- and high-temperature phases. Jump lengths, residence times, diffusion coefficients, and activation energies are extracted and compared to the crystal structure to uncover the diffusion pathways. We find that the hydrogen jump distances, residence times, and energy barriers become reduced following the phase transition, allowing for the efficient conduction of hydride ions through a series of hydrogen jumps of length L = 3.1 Å.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Evaluation of obstacle modelling approaches for resource assessment and small wind turbine siting: case study in the northern Netherlands

Abstract. Growth in adoption of distributed wind turbines for energy generation is significantly impacted by challenges associated with siting and accurate estimation of the wind resource. Small turbines, at hub heights of 40 m or less, are greatly impacted by terrestrial obstacles such as built structures and vegetation that can cause complex wake effects. While some progress in high-fidelity complex fluid dynamics (CFD) models has increased the potential accuracy for modelling the impacts of obstacles on turbulent wind flow, these models are too computationally expensive for practical siting and resource assessment applications. To understand the efficacy of available models in situ, this study evaluates classic and commonly used methods alongside new state-of-the-art lower-order models derived from CFD simulations and machine learning approaches. This evaluation is conducted using a subset of an extensive original dataset of measurements from more than 300 operational wind turbines in the northern Netherlands. The results show that data-driven methods (e.g. machine learning and statistical modelling) are most effective at predicting production at real sites with an average error in annual energy production of 2.5 %. When sufficient data may not be available de novo to support these data-driven approaches, models derived from high-fidelity simulations show promise and reliably outperform classic methods. On average these models have 6.3 %–11.5 % error compared with 26 % for classic methods and 27 % baseline error for reanalysis data without obstacle correction. While more performant on average, these methods are also sensitive to the quality of obstacle descriptions and reanalysis inputs.

17 WIND ENERGY↗

DOE OSTI2022

Internal rotation of ELM filaments on NSTX

Edge localized modes (ELMs) are a threat to tokamaks due to their high heat and particle loads on plasma facing components. A significant portion of this energy is carried and deposited by the emerging ELM filaments, whose dynamics are directly connected to their impact. Therefore, understanding their underlying physics is important for the operation of future fusion reactors. Our paper extends our knowledge of ELM filaments by reporting on their internal rotation (spinning) around the magnetic field lines along which they are extended. Our analysis of gas-puff imaging data on National Spherical Torus Experiment shows that ELM filaments are characterized by internal rotation in the direction of the ion-gyromotion with ω = 15:2 krad/s median angular velocity, which is approximately three times faster than the blob rotation in the background turbulence. The characteristic size of the ELM filament was also assessed and found to be similar to the blobs. A nearly linear trend was found between the angular velocity and the radial velocity of the ELM filament. The angular velocity was found to be linearly dependent on the distance of the filament from the separatrix, as well. An analytical model called the shear-induced rotation model was identified as a candidate for explaining the physics of the observations. Our results show that the modeled mechanism could significantly influence the rotation of the ELM filament; however, it cannot be a sole contributor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Optimized Renewable Energy Integration for EV High-Power Dynamic Wireless Charging Systems

Dynamic wireless charging for electric vehicles is an emerging technology to reduce on-board battery size and extend driving range. Due to its unique characteristic of vehicle-speed-related pulse-like load profile, the high-power dynamic wireless charging system (DWCS) introduces high stress to the utility grid. In this paper, an optimization model for renewable energy integration in the DWCS is proposed to mitigate the grid impact and minimize the operation costs of the whole system. As the load profile of DWCS is related to the traffic volume and various approaching vehicle speeds, the annual average daily traffic data and a stochastic model are used to develop 24-hour load profile of DWCS. To find a tradeoff between grid impact mitigation and operation costs minimization, relationships among power demand from power grid, photovoltaic (PV) capacity, wind energy (WE) capacity and energy storage (ES) capacity are analyzed, and the optimization objective and constraints are developed. Numerical simulation results demonstrate that energy storage integration can greatly mitigate the grid impact of DWCS, and optimal ratio of PV and WE can significantly reduce the operation cost of DWCS.

Zeng, Rong↗

DOE OSTI2024

The Nonradiative Properties of Self–Trapped Holes in Ultra–Wide Bandgap Gallium Oxide Film

The photoluminescence (PL) of self-trapped holes (STH) in ultra-wide bandgap β-Ga 2 O 3 is commonly its most dominant light emission and is an inherent property. Thus, gaining knowledge of the crystal dynamics that impact the PL properties is vital to sensor and other technologies. The PL, Raman-phonons, and their interactions are studied at an extreme temperature range of 77–622 K. The PL is studied up to the bandgap value of ≈5 eV. It is found that the high-energy Raman modes provide a major route to the nonradiative process of the PL via STH–phonon interaction with an activation energy of 72 meV. This dynamic is modeled with the configurational coordinate scheme at the strong phonon coupling limit. The exceptionally broad Gaussian PL linewidth manifests this coupling. The weak temperature response of the PL energy peak position indicates that the STH has characteristics of a deep-level defect. This contrasts with the large redshift of ≈220 meV of the optical gap of the film, ascertained from transmission. Unlike the temperature response of the high-energy phonons, the behavior of the low-energy phonons is found to follow the Bose–Einstein population increase, indicating no strong interaction with the STH.

Raman↗

DOE OSTI2021

Understanding the dynamics of vacuole trafficking and secretion for enhanced plant storage reserves

Vacuoles are essential in plants and serve roles in both protein and organelle degradation for reutilization and storage of high energy molecules such as storage proteins which are critical for seed germination under normal and stress conditions and impact biomass production and nutrition. In addition, plants secrete many different molecules such as cell wall components, lipids, waxes and others that are important for plant protection, structure and biomass. Vacuole accumulation and secretion are closely linked and highly regulated pathways within the endomembrane trafficking network. We have discovered many drug-like synthetic small molecules that can suppress vacuole trafficking and enhance secretion; other chemicals can enhance vacuole trafficking and suppress secretion. The ability of our compounds to modulate these pathways indicates that these pathways are tightly coupled and highly regulated. Thus, to achieve the goals of enhanced energy reserves or enhanced secretion it is essential to understand how this dynamic is controlled. Bioactive chemicals have provided us unique insight into natural mechanisms controlling the dynamics of vacuole trafficking and secretion that was not possible previously. One such compound, ES2, negatively modulates secretion while enhancing vacuole trafficking. This is the first compound discovered that targets an essential secretory complex known as the exocyst and will reveal important regulatory domains controlling secretion and vacuole trafficking. During the current funding period, we determined the structure of the EXO70A1 in plants and identifying its binding site. To understand the dynamics of vacuole trafficking it is key to have compounds that inhibit vacuole trafficking as well as enhancing it (ES2). We have used sophisticated image analysis to identify another novel compound ES17 that enhances secretion while negatively modulating vacuole trafficking (opposite of ES2). We have already made rapid progress. Our preliminary data indicates that ES17 very specifically targets a late stage of vesicle fusion with the tonoplast which is highly regulated. Thus, ES17 is an ideal compound to dissect the regulation of vacuole targeting dynamics. In addition, we have now synthesized a biotinylated version of ES17 that is fully functional, permitting the use of chemical proteomics to identify the cognate target with a high probability of success. We propose to investigate the ES17 target which can negatively modulate vacuole trafficking and combine this with knowledge of the ES2 target which can promote vacuole trafficking. Dissecting the mechanisms controlling the dynamics of secretion vs vacuole accumulation and the use of synthetic modulators will permit us to understand and regulate trafficking to enhance secretion to the plasma membrane and cell wall or the accumulation of biological energy reserves for increased biomass, nutritional value, stress resistance, and the secretion of specialized plant products.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

3D modeling of the Staged Z-pinch with the FLASH code

The Staged Z-pinch (SZP) fusion concept is a magneto-inertial compression scheme developed by Magneto-Inertial Fusion Technologies, Inc. (MIFTI), in which small amounts of fusion fuel are brought to fusion-relevant conditions by passing multi-million amperes strong current through a cylindrical shell of high atomic number material. One- and two-dimensional modeling performed by MIFTI with the MACH2 code, suggests that net fusion energy gain can be achieved when currents in the 10 million amperes range compress a 50%-50% mixture of deuterium and tritium gas. In this project we enhance and use the FLASH code to execute high-fidelity, simulations of various SZP configurations, a collaboration between the Flash Center for Computational Science at the University of Rochester and the Laboratory for Laser Energetics, and MIFTI. FLASH is a high-performance computing, multi-physics, radiation magnetohydrodynamic (MHD) code with extended physics capabilities, which is developed at the Flash Center. The goal of this project is to assess the shell/fuel stability of the pinch to two- and three-dimensional MHD instabilities and to utilize FLASH’s extended physics capabilities to understand how extended-MHD effects impact implosion dynamics and plasma conditions at stagnation. The project is a natural extension of an ongoing collaborative effort between MIFTI and the Flash Center through the U.S. DOE Advanced Research Projects Agency-Energy (ARPA-E) BETHE program and can provide MIFTI with simulation capabilities that are currently beyond their reach with MACH2. Ultimately, MIFTI wants FLASH to become one of their simulation workhorses for reliable, high-fidelity SZP platform design. During the project, the Flash Center team developed a suite of in one- and two-dimensional FLASH simulations to model different variants of the SZP platform, performed code-to-code comparisons with MACH2, and used the FLASH code to design and model SZP experiments like the Double Eagle experiments that MIFTI recently performed. Also, the Flash Center team developed the capabilities of FLASH to be able to do three-dimensional simulations of pulsed-power experiments with the code for the first time. Two publications from this effort are currently under review and two more are in preparation. MIFTI has also committed to the use of FLASH for future SZP simulation efforts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2010

Layered Model for Radiation-Induced Chemical Evolution of Icy Surface Composition on Kuiper Belt and Oort Cloud Bodies

The diversity of albedos and surface colors on observed Kuiper Belt and Inner Oort Cloud objects remains to be explained in terms of competition between primordial intrinsic versus exogenic drivers of surface and near-surface evolution. Earlier models have attempted without success to attribute this diversity to the relations between surface radiolysis from cosmic ray irradiation and gardening by meteoritic impacts. A more flexible approach considers the different depth-dependent radiation profiles produced by low-energy plasma, suprathermal, and maximally penetrating charged particles of the heliospheric and local interstellar radiation environments. Generally red objects of the dynamically cold (low inclination, circular orbit) Classical Kuiper Belt might be accounted for from erosive effects of plasma ions and reddening effects of high energy cosmic ray ions, while suprathermal keV-MeV ions could alternatively produce more color neutral surfaces. The deepest layer of more pristine ice can be brought to the surface from meter to kilometer depths by larger impact events and potentially by cryovolcanic activity. The bright surfaces of some larger objects, e.g. Eris, suggest ongoing resurfacing activity. Interactions of surface irradiation, resultant chemical oxidation, and near-surface cryogenic fluid reservoirs have been proposed to account for Enceladus cryovolcanism and may have further applications to other icy irradiated bodies. The diversity of causative processes must be understood to account for observationally apparent diversities of the object surfaces.

Cooper, John F.↗

NASA NTRS2010

Layered Model for Radiation-Induced Chemical Evolution of Icy Surface Composition and Dynamics on Kuiper Belt and Oort Cloud Bodies

The diversity of albedos and surface colors on observed Kuiper Belt and Inner Oort Cloud objects remains to be explained in terms of competition between primordial intrinsic versus exogenic drivers of surface and near-surface evolution. Earlier models have attempted without success to attribute this diversity to the relations between surface radiolysis from cosmic ray irradiation and gardening by meteoritic impacts. A more flexible approach considers the different depth-dependent radiation profiles produced by low-energy plasma, suprathermal, and maximally penetrating charged particles of the heliospheric and local interstellar radiation environment. Generally red objects of the dynamically cold (low inclination, circular orbit) Classical Kuiper Belt might be accounted for from erosive effects of plasma ions and reddening effects of high energy cosmic ray ions, while suprathermal keV-MeV ions could alternatively produce more color neutral surfaces. The deepest layer of more pristine ice can be brought to the surface from meter to kilometer depths by larger impact events and potentially by cryovolcanic activity. The bright surfaces of some larger objects, e.g. Eris, suggest ongoing resurfacing activity. Cycles of atmospheric formation and surface freezeout can further account for temporal variation as observed on Pluto. The diversity of causative processes must therefore be understood to account for observationally apparent diversities of the object surfaces.

Cooper, John F.↗

DOE OSTI2026

Evaluating Fracture Behavior of Bioinspired Alumina-YSZ Composites through Static and Dynamic Mechanical Testing

Ceramic materials are known for their high hardness and strength but are limited by low toughness and sudden failure. Inspired by the microstructure of dental enamel, which features undulating rods that promote crack deflection and energy absorption, architected specimens were designed and manufactured. A bespoke ball-on-ring (BoR) testing apparatus measured the static biaxial rupture strength of these bioinspired materials. Additionally, impact testing with spherical steel projectiles assessed their behavior under dynamic conditions. Monolithic alumina specimens were compared to architected alumina reinforced with yttria-stabilized zirconia (YSZ) rods produced via direct ink write 3D printing. BoR tests revealed that monolithic alumina had a Weibull modulus of 10.53 and a characteristic strength of 372.3 MPa, while the composite specimens showed a Weibull modulus of 5.46 and a characteristic strength of 213.3 MPa. Although the composite failed at lower stresses and projectile velocities, it exhibited notable crack deflection and fracture resistance, with cracks being effectively interrupted by the rod inclusions. The composite specimens also resulted in fewer and larger fragments upon impact. Finite element simulations confirmed the effectiveness of the rod structures in enhancing fracture resistance.

Bioinspired materials↗

DOE OSTI2021

Robust Large-Scale Dynamic Windows using Reversible Metal Electrodeposition

This project funded the study and development of dynamic windows based on reversible metal electrodeposition (RME). Dynamic windows allow user control over light and heat flow into and out of buildings, which offer both advantages in building aesthetics (with worker productivity improvement of 2%) and energy efficiency (up to 20% savings) compared to static controls such as low emissivity coatings and blinds/shades. Despite these advantages, dynamic windows, which traditionally rely on electrochromic metal oxides or conductive organic molecules for light modulation have failed to significantly impact the market due to issues related to cost, color, and optical dynamic range. Dynamic windows based on reversible metal electrodeposition (RME) are an exciting alternative approach and have the potential to overcome the issues associated with traditional technologies. A RME dynamic window is an electrochemical cell that modulates light using the reversible electrodeposition of metal on and off a transparent conducting oxide (TCO), which serves as the working electrode. The electrolyte has nearly colorless metal salts dissolved, and application of a cathodic potential on the TCO reduces the metal cations across the TCO surface to their metallic form, making a thin film that is efficient at blocking out light. A reverse in polarity oxidizes the metal, where it dissolves into solution, returning the window back to transparent. The counter electrode typically employed is a metal mesh, which is used to balance the electrochemical reactions happening on the TCO working electrode. These RME dynamic windows have the largest dynamic range (capable of reaching <<0.1% transmission) with color neutral tinting of any existing technology using solution processed techniques, which positions the technology as a promising candidate to penetrate the residential market. We have successfully scaled up the windows from 25 cm2 to 929 cm 2 , and we have demonstrated significant improvements to both the cycle life (10,000 cycles in a 3-electrode half-cell) and shelf life (>1 month) of our windows. We have published our work in high impact journals (6 published and 2 manuscripts in prep), filed 5 patents, and have incorporated TYNT Technologies to commercialize the technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Tracking Local pH Dynamics during Water Electrolysis via In-Line Continuous Flow Raman Spectroscopy

The performance of electrochemical devices, which play a critical role in decarbonization efforts, is often governed by proton-coupled electron transfer reactions at the electrode–electrolyte interface. These reactions are highly sensitive to the complex and dynamic microenvironment present at the electrode surface. However, characterizing this environment─particularly monitoring interfacial pH and its evolution under reaction conditions─remains challenging, necessitating the development of advanced analytical tools. Here, in this study, we introduce in-line continuous flow Raman spectroscopy (CFRS) as a spectroelectrochemical platform for quantifying interfacial pH swings generated during water-splitting. By monitoring phosphate ion speciation and controlling the hydrodynamics with a flow cell, we measure pH swings as a function of current density, flow rate, and distance from the electrode. Comparison with theoretical models reveals the impact of bulk pH, boundary layer thickness, and bubble dynamics at high current densities. Collectively, these findings establish CFRS as a platform for quantitatively investigating pH dynamics, offering critical insights for advancing electrochemical energy conversion technologies.

Marquez, Raul A. [Univ. of Texas, Austin, TX (Unit↗

DOE OSTI2026

Impact of high-fidelity temperature feedback modeling on fusion blanket neutronics

Accurate modeling and simulation of neutron and gamma transport and interactions within fusion tokamaks represents a critical area of research for fusion energy development. This paper presents a method to couple computational fluid dynamics (CFD) results to high-fidelity neutronics analyses, to explore the fusion neutronics’ feedback to blanket temperature and density. This method is demonstrated on a sector model of a tokamak with immersion molten salt blanket, and the relative differences in tritium breeding ratio (TBR) with spatially-resolved temperature modeling are explored. Additionally, the influence of higher fidelity neutronics results on the subsequent CFD analysis is explored. Results show that global TBR changes $<$0.1% due to temperature spatial distribution modeling. However, local TBR in areas with high temperature variability can have up to ∼4% difference.

blanket fusion↗

DOE OSTI2024

He bubble-induced phase transformation of W grain boundaries revealed by accelerated molecular dynamics

The growth of He bubbles and the resulting impact on the microstructural evolution of W are of paramount importance to the plasma-facing materials community due to the application of W in Tokamak fusion reactors. Using accelerated molecular dynamics (AMD) techniques, we outline the structural evolution of grain boundaries (GBs) caused by growing He bubbles. It is discovered that when an alternative, low energy, high density GB structure or phase is available, He bubbles can induce a progressive phase transformation of the GB to the higher density phase by the continual nucleation of W Frenkel pairs. Here, we find that the resulting W self-interstitials migrate to sites at the GB which are structurally related to the higher density phase, leading to the transformation. We discuss the implications of this progressive microstructural evolution on the growing He bubble and consider in general how He bubbles will impact the structural evolution of an arbitrary W GB. These findings of GB phase transformation are predicted to impact other damage events in W such as recrystallization, GB migration and defect segregation which must take these findings into account in order to accurately simulate a realistic W microstructure and hence extract experimentally meaningful data.

36 MATERIALS SCIENCE↗

NASA NTRS2009

Stellar Imager (SI): Enhancements to the Mission Enabled by the Constellation Architecture (Ares I/Ares V)

Stellar Imager (SI) is a space-based, UV/Optical Interferometer (UVOI) with over 200x the resolution of HST. It will enable 0.1 milli-aresec spectral imaging of stellar surfaces and the Universe in general and open an enormous new "discovery space" for astrophysics with its combination of high angular resolution, dynamic imaging , and spectral energy resolution. SI's goal is to study the role of magnetism in the Universe and revolutionize our understanding of 1) Solar/Stellar Magnetic Activity and their impact on Space Weather, Planetary Climates, and Life, 2) Magnetic and Accretion Processes and their roles in the Origin & Evolution of Structure and in the Transport of Matter throughout the Universe, 3) the close-in structure of Active Galactic Nuclei and their winds, and 4) Exo-Solar Planet Transits and Disks. SI is a "Landmark-Discovery Mission" in 2005 Heliophysics Roadmap and a candidate UVOI in the 2006 Astrophysics Strategic Plan and is targeted for launch in the mid-2020's. It is a NASA Vision Mission and has been recommended for further study in a 2008 NRC report on missions potentially enabled/enhanced by an Ares V launch. In this paper, we discuss the science goals and required capabilities of SI, the baseline architecture of the mission assuming launch on one or more Delta rockets, and then the potential significant enhancements to the SI science and mission architecture that would be made possible by a launch in the larger volume Ares V payload fairing, and by servicing options under consideration in the Constellation program.

Carpenter, Kenneth G.↗

DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗