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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

NSO Processing Scripts (NSO wind loading data set processing scripts) [SWR-23-86]

NREL conducted comprehensive field measurements of the atmospheric turbulent wind conditions and the resulting structural wind loads on parabolic troughs at the Nevada Solar One plant from October 2021 to June, 2023. The measurement set-up included meteorological masts and structural load sensors on four trough rows. Additionally, NREL commissioned a lidar scanning the horizontal plane over the trough field. The high-resolution data set, characterizing the complex flow field and resulting structural loads, is available at https://data.openei.org/submissions/5938. The processing routines published here were used to create the data from the instruments' raw data.

Egerer, Ulrike↗
DOE OSTI2022

Techniques for collective operations in distributed systems

Various embodiments are generally directed to techniques for collective operations among compute nodes in a distributed processing set, such as by utilizing ring sets and local sets of the distributed processing set. In some embodiments, a ring set may include a subset of the distributed processing set in which each compute node is connected to a network with a separate router. In various embodiments, a local set may include a subset of the distributed processing set in which each compute node is connected to a network with a common router. In one or more embodiments, each compute node in a distributed processing set may belong to one ring set and one local set.

Langer, Akhil↗
DOE OSTI2021

Binder Jet Printing of H13 Tool Steel

ORNL and Carpenter worked on evaluating H13 powders with different powder size distributions for deposition via binder jet additive manufacturing (AM). Binder jet AM has the potential to be a costeffective technique for fabrication of near net shaped tools with complex geometries and internal features such as cooling channels that can improve the production efficiency of injection/compression molding tools. However, a critical challenge in binder jet AM is the densification of the said tool for it to be usable. Powder size distribution can affect the process settings required to deposit the material and the subsequent sintering behavior. In this collaborative effort ORNL and Carpenter demonstrated that the process variables depend on the powder size distribution while the carbon pickup during sintering depends on the binder burnout atmosphere and temperature. On the other hand, there was no noticeable difference in the microstructural evolution of H13 deposited using the different powder size distributions.

42 ENGINEERING↗
DOE OSTI2022

Nonradiative Recombination via Charge-Transfer-Exciton to Polaron Energy Transfer Limits Photocurrent in Organic Solar Cells

Here, a recombination and exciton loss mechanism is reported in organic solar cells involving energy transfer between charge transfer (CT) excitons and polarons, impacting photocurrent generation, particularly in the near-infrared where polaronic transitions typically reside. This process sets a low-energy cut-off in the external quantum efficiency spectrum of an excitonic donor/acceptor interface, determined by the low-energy polaron absorption peak and the CT state reorganization energy. Furthermore, this process explains the deviation from unity and bias dependence of the CT state's internal quantum efficiency at low photon energies. This process is demonstrated in a variety of systems and it is hypothesized that CT state to polaron energy transfer recombination may be responsible for a share of nonradiative recombination in all organic photovoltaics and can explain numerous experimentally observed device trends regarding photocurrent generation and energy losses. Overall, this work enhances the understanding of photophysical processes in organic materials and allows the design of systems that can avoid this recombination pathway.

14 SOLAR ENERGY↗
DOE OSTI2021

Higgs flavor phenomenology in a supersymmetric left-right model with parity

In this paper, we focus on the supersymmetric model with left-right (LR) symmetry, that is especially proposed in our previous work [ 1 ]. In this model, there are four Higgs doublets in order to realize the Standard Model (SM) fermion masses and the Cabibbo-Kobayashi-Maskawa matrix. The heavy Higgs doublets unavoidably have flavor changing couplings to the SM fermions and induce flavor-changing neutral currents at tree level. We study broader parameter space than the previous work with including the renormalization group corrections to the Yukawa couplings between the LR breaking scale, \( \mathcal{O} \) (10 13 ) GeV, and the supersymmetry breaking scales, \( \mathcal{O} \) (100) TeV. The CP violating observable in K – \( \overline{K} \) mixing, ϵ K , strongly constrains the model, so that heavy Higgs mass should be heavier than \( \mathcal{O} \) (100) TeV. We study the lepton flavor violating (LFV) processes setting heavy Higgs masses to be 170 TeV. The branching ratios of μ → 3 e and the μ – e conversion can be larger than 10 - 16 that could be covered by the future experiments. We also study the degree of fine-tuning in the parameter region that predicts testable LFV processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Process and feedstock driven microstructure for laser powder bed fusion of 316L stainless steel

Here in the pursuit of improving additively manufactured (AM) component quality and reliability, fine-tuning critical process parameters such as laser power and scan speed is a great first step toward limiting defect formation and optimizing the microstructure. However, the synergistic effects between these process parameters, layer thickness, and feedstock attributes (e.g. powder size distribution) on part characteristics such as microstructure, density, hardness, and surface roughness are not as well-studied. In this work, we investigate 316L stainless steel density cubes built via laser powder bed fusion (L-PBF), emphasizing the significant microstructural changes that occur due to altering the volumetric energy density (VED) via laser power, scan speed, and layer thickness changes, coupled with different starting powder size distributions. This study demonstrates that there is not one ideal process set and powder size distribution for each machine. Instead, there are several combinations or feedstock/process parameter ‘recipes’ to achieve similar goals. This study also establishes that for equivalent VEDs, changing powder size can significantly alter part density, GND density, and hardness. Through proper parameter and feedstock control, part attributes such as density, grain size, texture, dislocation density, hardness, and surface roughness can be customized, thereby creating multiple high-performance regions in the AM process space.

316L stainless steel↗
DOE OSTI2019

Printed Conductive Transparent Films for the Fabrication of Sensors by Aerosol Inkjet Systems

Fabrication of sensors using additive manufacturing printers holds the promise for low-cost sensors for continuous and real time monitoring of physical and chemical parameters in industrial settings. Aerosol inkjet systems have demonstrated the capability to print small feature sizes with high precision using a variety of materials. Here, advances in nanomaterials suitable for use by such printers raises the possibility of having transparent, conductive films and sensors. Typically, transparent conductive films are fabricated using metallic oxides and complicated procedures on rigid substrates. In this paper, we present the results of the combination of silver nanowires formulations and aerosol inkjet systems for the fabrication of transparent conductive films by printing and its characterization. Implications for utilization of conductive, transparent sensors in manufacturing and industrial processes settings are discussed.

42 ENGINEERING↗
DOE OSTI2019

Printed Conductive Transparent Films for the Fabrication of Sensors by Aerosol Inkjet Systems

Fabrication of sensors using additive manufacturing printers holds the promise for low-cost sensors for continuous and real time monitoring of physical and chemical parameters in industrial settings. Aerosol inkjet systems have demonstrated the capability to print small feature sizes with high precision using a variety of materials. Advances in nanomaterials suitable for use by such printers raises the possibility of having transparent, conductive films and sensors. Typically, transparent conductive films are fabricated using metallic oxides and complicated procedures on rigid substrates. In this paper, we present the results of the combination of silver nanowires formulations and aerosol inkjet systems for the fabrication of transparent conductive films by printing and its characterization. Further, implications for utilization of conductive, transparent sensors in manufacturing and industrial processes settings are discussed.

42 ENGINEERING↗
DOE OSTI2023

Scalar Co-SIMP dark matter: models and sensitivities

In this work, we present UV completions of the recently proposed number-changing Co-SIMP freeze-out mechanism. In contrast to the standard cannibalistic-type dark matter picture that occurs entirely in the dark sector, the 3 → 2 process setting the relic abundance in this case requires one Standard Model particle in the initial and final states. This prevents the dark sector from overheating and leads to rich experimental signatures. We generate the Co-SIMP interaction with a dark sector consisting of two scalars, with the mediator coupling to either nucleons or electrons. In either case, the dark matter candidate is naturally light : nucleophilic interactions favor the sub-GeV mass range and leptophilic interactions favor the sub-MeV mass range. Viable thermal models in these lighter mass regimes are particularly intriguing to study at this time, as new developments in low-threshold detector technologies will begin probing this region of parameter space. While particles in the sub-MeV regime can potentially impact light element formation and CMB decoupling, we show that a late-time phase transition opens up large fractions of parameter space. These thermal light dark matter models can instead be tested with dedicated experiments. We discuss the viable parameter space in each scenario in light of the current sensitivity of various experimental probes and projected future reach.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Effect of laser melt schedule on the microstructure of additively manufactured IN718 Superalloy

Laser powder bed fusion (L-PBF) has enabled the fabrication of geometrically complex metallic structures and components that are challenging to producing using conventional manufacturing approaches. The site-specific and far from equilibrium thermal conditions of L-PBF offer the potential to facilitate multi-length scale design of structure and properties across the atomic-through macro-levels. However, L-PBF systems face scalability challenges due to throughput constraints. Laser rotary powder bed fusion (L-RPBF) systems are being investigated as a solution to enhance the deposition rates compared to conventional L-PBF. Rotary systems also offer additional flexibility for controlling the time structure of melting through laser interleaving on alternating layers. Here, in this study, IN718 test samples were printed using single-laser or interleaved dual-laser configuration in a L-RPBF system to investigates the effect of process settings and melt-interleaving on as-fabricated microstructure. The microstructural evolution, such as grain size and crystallographic texture, was assessed by determining variations in the melt-pool shapes. Laser interleaving leads to a reduction in average grain size compared to single laser by ∼ 40 % at high power (400 W) and by ∼36 % at medium power (370 W). Results presented here identify key challenge for obtaining uniform microstructures and barriers for the broader adoption of high-deposition rate L-RPBF.

Dual-laser↗
DOE OSTI2020

Accelerating nuclear fuel development and qualification: Modeling and simulation integrated with separate-effects testing

In this work, an approach to transform and accelerate nuclear fuel development and qualification is outlined. The approach exploits advanced modeling and simulation at the outset to inform constituent and system selection and to enable integral fuel performance analyses. Analyses using these tools identify and prioritize the most important fuel performance parameters and phenomena for subsequent targeted characterization with separate-effects tests. Separate-effects testing spans out-of-pile and in-pile tests and is meant to iterate with and inform engineering-scale integral fuel performance analyses throughout the development process. Exercising this cycle in an agile fashion will increase confidence in the integral fuel performance predictions while reducing uncertainties. This process sets the stage for executing a much more limited set of well-defined integral irradiation tests designed to validate engineering-scale fuel performance codes and to confirm the performance and safety of the fuel system under prototypic conditions. This approach will reduce the time for development and qualification of a new fuel system, and it will also reduce associated costs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Optics-Free Chip-Scale Intraoperative Imaging Using NIR-Excited Upconverting Nanoparticles

Here we present an optics-free CMOS image sensor that incorporates a novel time-gated dual-photodiode pixel design to allow filter- and lens-less image acquisition of near-infrared-excited (NIR-excited) upconverting nanoparticles. Recent biomedical advances have highlighted the benefits of NIR excitation, but NIR interaction with silicon has remained a challenge, even with high-performance optical blocking filters. Using a secondary diode and a dual-photodiode design, this sensor is able to remove the 100s of mV of NIR background on pixels and bring it down to single-digit mV level, nearing its noise floor of 2.2 mV rms, not achievable with any optical filter. Non-linear effects of background cancellation using the diode pair has been mitigated using an initial one-time pixel-level curve fitting and calibration in a post-processing setting. This imager comprises a highly linear 11 fF metal-oxide-metal (MOM) capacitor and includes integrated angle-selective gratings to reject oblique light and enhance sharpness. Each pixel also includes two distinct correlated double sampling schemes, to remove low frequency flicker noise and systematic offset in the datapath. We demonstrate the performance of this imager using pulsed NIR-excited upconverting nanoparticles on standard United-States-Air-Force (USAF) resolution targets and achieve an SNR of 15 dB, while keeping NIR background below 6 mV. This 36-by-80-pixel array measures only 2.3 mm by 4.8 mm and can be thinned down to 25 µm, allowing it to become surgically compatible with intraoperative instruments and equipment, while remaining optics-free.

42 ENGINEERING↗
DOE OSTI2026

Understanding the Thermal Physics and Metallurgy of Metal Big Area Additive Manufacturing

The research goal of this EPSCoR-DOE partnership is to mitigate defects in parts made using a new type of additive manufacturing (AM) process called metal Big Area Additive Manufacturing (m-BAAM). To realize this goal, the PIs will detect and correct defects in the part as it is being printed by combining fundamental knowledge of the thermal physics and metallurgy of m-BAAM with in-process sensor data. Developed at the DOE-funded Manufacturing Demonstration Facility at Oak Ridge National Laboratory, the m-BAAM process involves one or more robots working together to produce a part by fusing metal wire layer-by-layer using arc welding. The process can print large metal parts such as turbine blades, which is not possible using other AM processes. In addition, m-BAAM production rates are more than ten times faster than other AM processes while requiring one-tenth of the material cost. Despite their potential to become a critical force multiplier in the energy generation industry, m-BAAM parts may fail to print accurately due to retention of heat and uneven cooling. Overheating and anomalous cooling rates in turn can cause inconsistencies in the microstructure, leading to sudden failure when used in safety-critical applications. In other words, flaw formation in m-BAAM parts is governed by the thermal history – intensity and spatial distribution of heat inside the part during printing. The thermal history is a complex function of the part shape and process settings such as welding energy, path taken by the welding torch for deposition (tool path), wire feed rate, among others.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Magnetic Field Sensing via Acoustic Sensing Fiber with Metglas® 2605SC Cladding Wires

Magnetic field sensing has the potential to become necessary as a critical tool for long-term subsurface geophysical monitoring. The success of distributed fiber optic sensing for geophysical characterization provides a template for the development of next generation downhole magnetic sensors. In this study, Sentek Instrument’s picoDAS is coupled with a multi-material single mode optical fiber with Metglas® 2605SC cladding wire inclusions for magnetic field detection. The response of acoustic sensing fibers with one and two Metglas® 2605SC cladding wires was evaluated upon exposure to lateral AC magnetic fields. An improved response was demonstrated for a sensing fiber with in-cladding wire following thermal magnetic annealing (~400 °C) under a constant static transverse magnetic field (~200 μT). A minimal detectable magnetic field of ~500 nT was confirmed for a sensing fiber with two 10 μm cladding wires. The successful demonstration of a magnetic field sensing fiber with Metglas® cladding wires fabricated via traditional draw processes sets the stage for distributed measurements and joint inversion as a compliment to distributed fiber optic acoustic sensors.

Dejneka, Zach (ORCID:0000000179415708)↗
DOE OSTI2023

Tutorial for Non-Orthogonal Configuration Interaction Fragment Studies Using GronOR

A brief tutorial is presented for the GronOR non-orthogonal configuration interaction application illustrating the download and build process, setting up calculations with OpenMolcas and GronOR, and a description of the file structure and input options. An overview of the computational workflow includes the generation of fragment wave functions and integrals with an adapted version of OpenMolcas, running GronOR calculations, and accounting for dynamic correlation corrections. Three end-to-end use cases are provided, representing a molecular dimer, an ion pair, and overlapping molecular fragments.

Straatsma, T.P.↗
DOE OSTI2021

Understanding the setting and hardening process of wollastonite-based brushite cement. Part 2: Influence of the boron and aluminum concentrations in the mixing solution

The mixing solution of wollastonite-based brushite cement is a phosphoric acid solution containing metallic cations and borax. This work complements a previous study devoted to the influence of the H{sub 3}PO{sub 4} concentration, Ca/P and liquid-to-solid (l/s) ratios on the setting and hardening process of the binder by providing new insight into the role of aluminum and boron. Boron retards the setting and decreases the heat released during the process. It also contributes to reduce the macroporosity of the hardened material but yields to poor compressive strength. With aluminum in the mixing solution, the mechanical properties are greatly improved thanks to the precipitation of an amorphous aluminophosphate which increases the density of the cement matrix. But aluminum alone leads to fast setting. A joint addition of boron and aluminum to the mixing solution makes it possible to get a material with optimized properties both in fresh and hardened states.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Reconstructing the Universe: Testing the Mutual Consistency of the Pantheon and SDSS/eBOSS BAO Data Sets with Gaussian Processes

We test the mutual consistency between the baryon acoustic oscillation measurements from the eBOSS SDSS final release and the Pantheon supernova compilation in a model-independent fashion using Gaussian process regression. We also test their joint consistency with the ΛCDM model in a model-independent fashion. We also use Gaussian process regression to reconstruct the expansion history that is preferred by these two data sets. While this methodology finds no significant preference for model flexibility beyond ΛCDM, we are able to generate a number of reconstructed expansion histories that fit the data better than the best-fit ΛCDM model. These example expansion histories may point the way toward modifications to ΛCDM. We also constrain the parameters Ω{sub k} and H {sub 0} r {sub d} both with ΛCDM and with Gaussian process regression. We find that H {sub 0} r {sub d} = 10,030 ± 130 km s{sup −1} and Ω{sub k} = 0.05 ± 0.10 for ΛCDM and that H {sub 0} r {sub d} = 10,040 ± 140 km s{sup −1} and Ω{sub k} = 0.02 ± 0.20 for the Gaussian process case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Thermal Image Processing for Feature Extraction from Encapsulated Phase Change Materials

Encapsulated inorganic particles with high melting points (>300 °C) are desired as high-temperature Phase Change Materials (PCMs) for next-generation Latent Heat Thermal Energy Storage (LHTES) systems. One of the many challenges during the development of PCMs is to achieve a high throughput that in turn depends on accurately modeling the relation between process parameters and geometric & thermal properties of the PCMs particle. During the production of the PCMs, a high-speed infrared camera is used to acquire images of the encapsulated material under controlled illumination conditions. This research article focuses on the development of image processing techniques for both geometric and thermal feature extraction during the development of the PCMs. A user-friendly GUI has been designed in MATLAB and preliminary experimental results have demonstrated that the method is fast, accurate and reliable for a high throughput production. The extracted features will be used to develop Machine Learning (ML) models to predict the geometric and thermal properties of the PCM based on the process parameter settings. The ML model will accelerate the search for the optimized process settings to boost the throughput of the production.

25 ENERGY STORAGE↗