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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Unwrapping Radiograph Target Disassembly Using Adaptive Machine Learning [Slides]

Advanced analysis methods were developed to determine the electron temperature and density evolution of targets disassembly by intense electron beams at DARHT based on shearing interferometer and shadowgraph measurements. New methods have been developed to spatially and temporally resolve electron velocity and temperature, expanding on recently published first results of Aluminum target disassembly. A surrogate model has been created for use in developing Adaptive Machine Learning analysis techniques. The results will also be used to guide the development of the system and experimental approach to future measurements on DARHT Axis-I and a new system to be deployed on DARHT Axis-II.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Compare low-gain 1D and 3D models toward a storage ring-based X-ray free-electron-laser oscillator

Fourth-generation diffraction-limited synchrotron light sources (DL-SLS) present a compelling platform for advanced light source applications due to their ultra-low emittance (around tens of picometers), sub-micrometer beam stability, and high repetition rates (greater than 1 MHz). Despite these advantages, fundamental limitations, such as long bunch durations (tens of picoseconds), large relative energy spread (~10⁻³), and low peak current (<300 A), have hindered their effectiveness in free-electron laser (FEL) applications. Using a low-gain three-dimensional (3D) model based on NSLS-II upgrade lattice parameters, we demonstrate that a 6% single-pass gain is achievable with an optimized transverse gradient undulator (TGU). Concurrently, recent advances in X-ray optics—specifically, a four-mirror bow-tie resonator utilizing diamond mirrors and beryllium compound refractive lenses (CRLs)—enable total round-trip losses below 4% and an output coupling efficiency near 1%, rendering a Storage Ring based X-ray FEL oscillator (XFELO) a realistic possibility. In the 3D framework, the TGU effectively mitigates the detrimental effects of large energy spread by spatially dispersing the beam, leading to enhanced gain relative to conventional one-dimensional (1D) models. We establish both analytical and numerical connections between the 1D and 3D descriptions, leveraging GENESIS simulations to map equivalent gain conditions. While 1D resonance is defined in the energy domain, the 3D TGU system shifts the resonance dependence to transverse gradient and dispersion parameters. Once optimized, this framework allows predictive modeling using 1D formulas, which can then be validated through full 3D simulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Deep-learning based artificial intelligence tool for melt pools and defect segmentation

Accelerating fabrication of additively manufactured components with precise microstructures is important for quality and qualification of built parts, as well as for a fundamental understanding of process improvement. Accomplishing this requires fast and robust characterization of melt pool geometries and structural defects in images. This paper proposes a pragmatic approach based on implementation of deep learning models and self-consistent workflow that enable systematic segmentation of defects and melt pools in optical images. Deep learning is based on an image-to-image translation–conditional generative adversarial neural network architecture. An artificial intelligence (AI) tool based on this deep learning model enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing-induced structural defects. We present statistical analysis of geometric features that is enabled by the AI tool, showing strong spatial correlation of defects and the melt pool boundaries. The correlations of widths and heights of melt pools with dataset processing parameters show the highest sensitivity to thermal influences resulting from laser passes in adjacent and subsequent layer passes. The presented models and tools are demonstrated on the aluminum alloy and datasets produced with different sets of processing parameters. However, they have universal quality and could easily be adapted to different material compositions. The method can be easily generalized to microstructural characterizations other than optical microscopy.

additive manufacturing↗
DOE OSTI2024

High resolution numerical simulations of methane pool fires using adaptive mesh refinement

The ability to accurately predict the structure and dynamics of pool fires using computational simulations is of great interest in a wide variety of applications, including accidental and wildland fires. However, the presence of physical processes spanning a broad range of spatial and temporal scales poses a significant challenge for simulations of such fires, particularly at conditions near the transition between laminar and turbulent flow. Here, in this study, we examine the transition to turbulence in methane pool fires using high-resolution simulations with multi-step finite rate chemistry, where adaptive mesh refinement (AMR) is used to directly resolve small-scale flow phenomena. We perform three simulations of methane pool fires, each with increasing diameter, corresponding to increasing inlet Reynolds and Richardson numbers. As the diameter increases, the flow transitions from organized vortex roll-up via the puffing instability to much more chaotic mixing associated with finger formation along the shear layer and core collapse near the inlet. These effects combine to create additional mixing close to the inlet, thereby enhancing fuel consumption and causing more rapid acceleration of the fluid above the pool. We also make comparisons between the transition to turbulence and core collapse in the present pool fires and in inert helium plumes, which are often used as surrogates for the study of buoyant reacting flows.

42 ENGINEERING↗
DOE OSTI2024

Filaments in and between galaxy clusters at low and mid-frequency with the SKA

Context. Understanding the magnetised Universe is a major challenge in modern astrophysics, and cosmic magnetism has been acknowledged as one of the key scientific drivers of the most ambitious radio instrument ever planned, the Square Kilometre Array. Aims. With this work, we aim to investigate the potential of the Square Kilometre Array and its precursors and pathfinders in the study of magnetic fields in galaxy clusters and filaments through diffuse synchrotron radio emission. Galaxy clusters and filaments of the cosmic web are indeed unique laboratories in which to investigate turbulent fluid motions and large-scale magnetic fields in action, and much of what is known about magnetic fields in galaxy clusters comes from sensitive radio observations. Methods. Based on cosmological magneto-hydrodynamic simulations, we predict radio properties (total intensity and polarisation) of a pair of galaxy clusters connected by a cosmic-web filament. Results. We use our theoretical expectations to explore the potential of polarimetric observations to study large-scale structure magnetic fields in the frequency ranges 50–350 MHz and 950–1760 MHz. We also present predictions for galaxy cluster polarimetric observations with the Square Kilometre Array precursors and pathfinders, such as the LOw frequency ARray 2.0 and the MeerKAT+ telescope. Conclusions. Our findings point out that polarisation observations are particularly powerful for the study of large-scale magnetic fields, since they are not significantly affected by confusion noise. The unprecedented sensitivity and spatial resolution of the intermediatefrequency radio telescopes make them the favourite instruments for the study of these sources through polarimetric data, potentially allowing us to understand if the energy density of relativistic electrons is in equipartition with the magnetic field or rather coupled with the thermal gas density. Our results show that low-frequency instruments also represent a precious tool to study diffuse synchrotron emission in total intensity and polarisation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Introduction to the special topic on inertial confinement fusion diagnostics

In the first decade of the 21st century, the United States began operating three leading Inertial Confinement Fusion (ICF) and High-Energy Density Physics (HEDP) facilities. The National Ignition Facility (NIF) began its quest to first surpass the Lawson Criterion and then reach thermonuclear ignition and thermonuclear gain. The Omega EP (Extended Performance) laser provides unprecedented energy, reliability, and consistency for petawatt (PW)-class laser experiments. The Omega laser continues to support over 1000 ICF and HEDP experiments each year. The Z pulsed power machine is a Z-pinch plasma confinement device that was refurbished to increase current drive and improve reliability. The extreme states of matter created in these new facilities required advancement of many technologies. The most important among these was the significant improvement in instrumentation capabilities needed to diagnose plasma conditions and resulting nuclear products. The instruments needed a better temporal, spatial, and energy resolution. They also needed to be hardened against EMP and radiation. Typical events in an ICF implosion include compressing the deuterium–tritium (DT) fuel to greater than 60 g/cm 3 and heating the DT to a temperature greater than 10 keV (110 000 000 K). The DT atoms react to produce 14 MeV neutrons from a volume with a radius of ~30 μm. When the fuel ignites, the DT burn prop agates into cold fuel and the neutron-emitting region can reach sizes of over 200 μm. Furthermore, the burn typically lasts less than 150 ps, but the burn duration will decrease as the DT yield increases. Burn durations as short as 90 ps have been recorded and are predicted to decrease still further to 20 ps. X-ray imaging diagnostics are needed to measure the acceleration and velocity of the capsule enclosing the DT, where the implosion velocities can reach over 400 km/s.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Evaluation of Two-Dimensional to One-Dimensional Site Response for Idaho National Laboratory

We perform two-dimensional (2D) site response analyses accounting for spatial variability of soil properties and subsurface geometry of the Eastern Snake River Plane (ESRP), and quantify their effects on ground surface motion relative to one-dimensional (1D) site response analyses at the Idaho National Laboratory (INL). We first present the development of random field idealizations of the repeated basalt lava flows, heterogeneously inter-layered with sediments, from seismic velocity data collected over four decades in the ESRP. Using realizations of the stochastic fields mapped on 2D deterministic finite element models, we perform 2D viscoelastic and equivalent-linear wave propagation simulations, and quantify the mean and variance of site response aggravation factors, defined as the response spectral ratio of 2D to 1D analyses on the ground surface. Results are shown to be insensitive to the constitutive material behavior considered here, for strains induced by rock outcrop peak ground acceleration (PGA) as high as 0.7g: viscoelastic and equivalent-linear analyses predict peak mean 2D/1D aggravation factor 1.05 at period T=0.075 sec (i.e. the 2D response spectrum is 5% higher than the corresponding 1D at that period, on average), which corresponds to the wavelength of the horizontal correlation length of the random field (50m). For periods longer than the fundamental period of the site (here, T 1 =0.3125 sec), the propagating wavelengths are too long to be affected by the 1D site response and the aggravation factor becomes equal to 1. The standard deviation of the natural logarithms of the 2D/1D aggravation factors is ~0.15 for periods shorter than the fundamental period of the site, and decays thereafter at a steady rate.

58 GEOSCIENCES↗
DOE OSTI2020

Organizing principles for vegetation dynamics

Understanding vegetation dynamics is very challenging because of the multitude of contributing processes at 64widely different spatial and temporal scales. In this Perspective we propose that understanding of vegetation dynamics can be improved, permitting better predictions, based on organizing principles that constrain plant and ecosystem be haviour: natural selection, self-organization, and entropy maximization. Although these ideas are increasingly used,a limited common understanding of their theoretical basis has prevented their full potential to be realized. We explain the power of natural selection-based optimality to predict photosynthesis and carbon allocation responses to multiple environmental drivers, and how individual plasticity leads to the predictable self-organization of forest canopies. We show how models of natural selection acting on a few key traits can generate realistic plant communities, and how entropy maximization can distinguish between stochastic and deterministic drivers of vegetation patterns. In combination with empirical exploration of patterns in plant functional variation, these principles can accelerate the development of dynamic vegetation models as well as trait-based ecology resting on strengthened theoretical and empirical foundations.

Geosciences↗
DOE OSTI2022

Magnetic Field Vector Measurements Using Doppler-Free Saturation Spectroscopy

Experimentally measuring the magnetic-field vector topology in low-cost fusion-concept devices will provide critical information required to optimize and accelerate the development of those concepts for economical fusion energy. The magnetic-field measurement techniques most commonly used in modern tokamaks, i.e., beam-emission spectroscopy and optical emission spectroscopy, are not suitable below 5000 Gauss due to a lack of sensitivity. To diagnose magnetic field relevant to some of the ARPA-E-supported fusion concepts (50 to 1000 Gauss), a novel approach is required. Doppler-free saturation spectroscopy (DFSS) is a pump/probe laser-based technique and has been successfully demonstrated in the laboratory to provide a magnetic-field measurement accuracy of <10 Gauss. DFSS is implemented to obtain ultra-high-resolution spectra at a localized point in space. The spectral data is then fit to the Schrödinger equation for determination of the magnetic-field vector. To obtain the magnetic-field topology, the measurement spatial location is scanned over the desired region of space by steering the DFSS pump laser beam. The goal of this project is to assemble and commission a portable DFSS diagnostic capable of 2-D magnetic-field vector measurements utilizing the Hα spectral line profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Smart sensors using artificial intelligence for on-detector electronics and ASICs

Cutting edge detectors push sensing technology by further improving spatial and temporal resolution, increasing detector area and volume, and generally reducing backgrounds and noise. This has led to a explosion of more and more data being generated in next-generation experiments. Therefore, the need for near-sensor, at the data source, processing with more powerful algorithms is becoming increasingly important to more efficiently capture the right experimental data, reduce downstream system complexity, and enable faster and lower-power feedback loops. In this paper, we discuss the motivations and potential applications for on-detector AI. Furthermore, the unique requirements of particle physics can uniquely drive the development of novel AI hardware and design tools. We describe existing modern work for particle physics in this area. Finally, we outline a number of areas of opportunity where we can advance machine learning techniques, codesign workflows, and future microelectronics technologies which will accelerate design, performance, and implementations for next generation experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Aerosol‐Jet‐Printable Covalent Organic Framework Colloidal Inks and Temperature‐Sensitive Nanocomposite Films

Abstract With molecularly well‐defined and tailorable 2D structures, covalent organic frameworks (COFs) have emerged as leading material candidates for chemical sensing, storage, separation, and catalysis. In these contexts, the ability to directly and deterministically print COFs into arbitrary geometries will enable rapid optimization and deployment. However, previous attempts to print COFs have been restricted by low spatial resolution and/or post‐deposition polymerization that limits the range of compatible COFs. Here, these limitations are overcome with a pre‐synthesized, solution‐processable colloidal ink that enables aerosol jet printing of COFs with micron‐scale resolution. The ink formulation utilizes the low‐volatility solvent benzonitrile, which is critical to obtaining homogeneous printed COF film morphologies. This ink formulation is also compatible with other colloidal nanomaterials, thus facilitating the integration of COFs into printable nanocomposite films. As a proof‐of‐concept, boronate‐ester COFs are integrated with carbon nanotubes (CNTs) to form printable COF‐CNT nanocomposite films, in which the CNTs enhance charge transport and temperature sensing performance, ultimately resulting in high‐sensitivity temperature sensors that show electrical conductivity variation by 4 orders of magnitude between room temperature and 300 °C. Overall, this work establishes a flexible platform for COF additive manufacturing that will accelerate the incorporation of COFs into technologically significant applications.

2D materials↗
DOE OSTI2023

Attaining freshwater and estuarine-water soil saturation in an ecosystem-scale coastal flooding experiment

Abstract Coastal upland forests are facing widespread mortality as sea-level rise accelerates and precipitation and storm regimes change. The loss of coastal forests has significant implications for the coastal carbon cycle; yet, predicting mortality likelihood is difficult due to our limited understanding of disturbance impacts on coastal forests. The manipulative, ecosystem-scale Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m 2 ), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. Transient saturation (5 h) of the entire soil rooting zone (0–30 cm) across a 2000 m 2 coastal forest was attained by delivering 300 m 3 of water through a spatially distributed irrigation network at a rate just above the soil infiltration rate. Our water delivery approach also elevated the water table (typically ~ 2 m belowground) and achieved extensive, low-level inundation (~ 8 cm standing water). A TEMPEST simulation approximated a 15-cm rainfall event and based on historic records, was of comparable intensity to a 10-year storm for the area. This characterization was supported by showing that Hurricane Ida’s (~ 5 cm rainfall) hydrologic impacts were shorter (40% lower duration) and less expansive (80% less coverage) than those generated through experimental manipulation. Future work will apply TEMPEST treatments to evaluate coastal forest resilience to changing hydrologic disturbance regimes and identify conditions that initiate ecosystem state transitions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A modeling study of ocean thermal energy conversion resource and potential environmental effects around Kailua-Kona, Hawaii

Ocean Thermal Energy Conversion (OTEC) offers a promising renewable energy solution through a heat exchange process using the temperature difference between warm surface seawater and cold deep seawater. Because accurate resource characterization is critical for the optimal design and implementation of OTEC systems, a high-resolution numerical model is employed to better characterize the OTEC resource at Kona, Hawaii. Our model provides detailed spatial and temporal variability of the thermal gradient, which is essential for assessing the viability and efficiency of OTEC systems. The model results reveal distinct patterns and dynamics not captured by existing observations or models (e.g., lower-resolution information). These findings highlight the importance of using high-resolution models for accurate predictions of thermal gradient variability, ultimately supporting more efficient and sustainable OTEC deployment. Additionally, the study investigates the impacts of mixed water discharge from OTEC plants that can cause shock to organisms living in the surface water and potentially destabilize the water column. Understanding these effects is vital for minimizing any potential negative environmental consequences and ensuring the long-term viability of OTEC operations. Further, our model improves OTEC resource characterization, which can lead to optimal design and deployment of OTEC systems. The analysis of OTEC water discharge impacts can accelerate the development of OTEC technologies, overcoming permitting/consenting challenges. These findings contribute to the broader adoption of high-resolution modeling in ocean energy resource characterization, particularly for OTEC applications.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

In planta single-molecule imaging and holographic force spectroscopy to study real-time, multimodal turnover dynamics of polysaccharides and associated carbohydrate metabolites

Cellular production of polysaccharides from simple sugar molecules serves critical roles in a variety of metabolic processes essential to the survival of every living organism. In the context of photosynthetically fixed carbon, cell wall polysaccharides synthesis is particularly of interest for increased biomass accumulation for human food, animal feed, and bioenergy related applications. Despite a long history of research in plant cell biology, our understanding of in planta cell wall biosynthesis and its regulation is far from complete due to lack of a comprehensive microscopy toolkit that encompass the multiple spatial and temporal scales in which cell wall polysaccharides fibrils are synthesized and assembled into intricate cell wall networks. In this project, a multidisciplinary team of scientists from Rutgers University, Vanderbilt University, and Oak Ridge National Laboratory carried out innovative multimodal, multiscale microscopy studies of cell wall synthesis using single-molecule force-spectroscopy, super-resolution fluorescence microscopy, and in vivo live cell imaging. Our novel multimodal and holistic imaging approach revealed plant cell wall polysaccharides synthesis processes in unprecedented detail across multiple spatiotemporal scales, from a single-molecule to a single-cell. Besides, the team has made technical and scientific innovations across multiple research fields—microscopy, bioengineering, single-molecule biophysics, and plant biology, etc.—to accomplish the goals. The results from this project will greatly advance the mechanistic and holistic understanding of in planta cell wall synthesis, which will accelerate the development of better transgenic crops for bioenergy applications. Moreover, the new toolbox, combining powerful advanced microscopy assays with cell/protein engineering, will have broader impacts on molecular and cellular biology fields by paving the way for studying cellular processes occurring across multiple physical scales with multimodal microscopy methodologies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Barriers and variable spacing enhance convective cooling and increase power output in solar PV plants

When the temperature of solar photovoltaic (PV) modules rises, efficiency drops and module degradation accelerates. Thus, it is beneficial to reduce module operating temperatures. Previous studies of solar power plants have illustrated that incoming flow characteristics, turbulent mixing, and array geometry can strongly impact convective cooling, as measured by the convective heat transfer coefficient h. In the fields of heat transfer and plant canopy flow, previous work has shown that system-scale arrangement modifications—e.g., variable spacing, barriers, or windbreaks—can passively alter the flow, enhance turbulent mixing, and influence convection. However, researchers have not yet explored how variable spacing or barriers might enhance convective cooling in solar power plants. Here, high-resolution large-eddy simulations model the air flow and heat transfer through solar power plant arrangements modified with missing modules and barrier walls. We then perform a control volume analysis to evaluate the net heat flux and compute h, which quantifies the influence of these spatial modifications on convective cooling and, thus, module temperature and power output. Installing barrier walls yields the greatest improvements, increasing h by 3.4%, reducing module temperature by an estimated 2.5 °C, and boosting power output by an estimated 1.4% on average. These findings indicate that incorporating variable spacing or barrier-type elements into PV plant designs can reduce module temperature and, thus, improve PV performance and service life.

14 SOLAR ENERGY↗
DOE OSTI2023

3P Program: Phenotyping X Prediction = Productivity (Final Scientific/Technical Report)

The goal of the 3P Program was to establish integrated, real-time phenotyping and to analyze above- and below-ground plant architecture and total carbon partitioning and allocation to predict heterosis and develop superior crop hybrids by fully leveraging the Sorghum gene pool. There were two overarching themes: 1) the development of a new crop improvement approach utilizing advances in high-throughput phenotyping (HTP), computing, and genomics for public dissemination and 2) leveraging this platform for sorghum crop improvement and commercialization. The Clemson team worked on creating genomic resources and using both statistical learning and high-throughput phenotyping in genomics-assisted breeding. Research was broadly interested in the genetics of carbon partitioning, with the aim of improving crop performance and achieving sustainability. The technology and resources created can be readily found in the public domain and serve to advance scientific understanding of crop genomics and breeding. Genomic prediction was able to identify top crosses to be made, and a hybrid prediction pipeline is in place to drive year-over-year genetic gain. Roots have long been ignored by plant breeders and agronomists, not because they are unimportant but because they are hard to measure. This is an untapped white space of potential insight and innovation. To address this, Hi Fidelity Genetics developed the RootTracker to measure roots in the field on a continuous basis. A database system called RootTracker Tracker was developed to handle data coming from the RootTrackers. In using this device, valuable data was observed for plant breeding, hydrochemical development, and other agricultural biology applications. Carnegie Mellon’s goal was developing new techniques to generate high-resolution 3D models of plants from data collected in the field. The idea was that more useful and more informative phenotypes could be extracted by resolving small features, such as seeds and flowers, and that by modeling in 3D, the spatial structure of plants could be examined. To achieve this, multiple images collected by a new small format structured light stereo imager were fused together. A sorghum panicle modeling pipeline was developed to allow the collection and processing of data. Carolina Seed Systems is an agricultural technology company focused on decarbonizing the agricultural system. Their technology pipeline serves to drive fundamental progress towards creation and distribution of carbon negative crops. The genomic and the engineering technology developed through the 3P Program was leveraged to deliver both value and sustainability from the grower to the consumer. Promising sorghum hybrids were scaled up and commercialized. The overall goal of our research was to integrate, create, and deploy genetic and engineering concepts and technologies to enhance crop productivity in a sustainable fashion. The combination of public and private partners allowed the basic research and hypothesis testing to be quickly accelerated for commercial application by the companies yet maintained that the core framework and academic insights remain in the public domain for continued market disruption, competition, and innovation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Atacama Cosmology Telescope: Multiprobe cosmology with unWISE galaxies and ACT DR6 CMB lensing

We present a joint analysis of the cosmic microwave background (CMB) lensing power spectra measured from the Data Release 6 of the Atacama Cosmology Telescope (ACT) and Planck PR4, cross-correlations between the ACT and Planck lensing reconstruction and galaxy clustering from unWISE, and the unWISE clustering auto-spectrum. We obtain 1.5% constraints on the matter density fluctuations at late times parametrized by the best constrained parameter combination 𝑆$^{3⁢x⁢2⁢pt}_{8}$ ≡ 𝜎 8 ⁢(Ω 𝑚 /0.3) 0.4 = 0.815 ± 0.012. The commonly used 𝑆 8 ≡ 𝜎 8⁢ (Ω 𝑚 /0.3) 0.5 parameter is constrained to 𝑆 8 = 0.816 ± 0.015. In combination with baryon acoustic oscillation (BAO) measurements we find 𝜎 8 = 0.815 ± 0.012. We also present sound-horizon-independent estimates of the present day Hubble rate of 𝐻 0 = 66.4$^{+3.2}_{−3.7}$ km s −1 Mpc −1 from our large scale structure data alone and 𝐻 0 = 64.3$^{+2.1}_{−2.4}$ km s −1 Mpc −1 in combination with uncalibrated supernovae from Pantheon+. Using parametric estimates of the evolution of matter density fluctuations, we place constraints on cosmic structure in a range of high redshifts typically inaccessible with cross-correlation analyses. Combining lensing cross- and autocorrelations, we derive a 3.3% constraint on the integrated matter density fluctuations above 𝑧 = 2.4, one of the tightest constraints in this redshift range and fully consistent with a Λ cold dark matter (Λ⁢CDM) model fit to the primary CMB from Planck. Finally, combining with primary CMB observations and using the extended low redshift coverage of these combined datasets we derive constraints on a variety of extensions to the Λ⁢CDM model including massive neutrinos, spatial curvature, and dark energy. We find in flat Λ⁢CDM⁢ ∑𝑚 𝜈 < 0.12 eV at 95% confidence using the large scale structure data, BAO measurements from Sloan Digital Sky Survey, and primary CMB observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Verification of diesel spray ignition phenomenon in dual-fuel diesel-piloted premixed natural gas engine

Dual-fuel (DF) engines, in which premixed natural gas and air in an open-type combustion chamber is ignited by diesel-fuel pilot sprays, have been more popular for marine use than pre-chamber spark ignition (PCSI) engines because of their superior durability. However, control of ignition and combustion in DF engines is more difficult than in PCSI engines. In this context, here we focus on the ignition stability of n-heptane pilot-fuel jets injected into a compressed premixed charge of natural gas and air at low-load conditions. To aid understanding of the experimental data, chemical-kinetics simulations were carried out in a simplified engine-environment that provided insight into the chemical effects of methane (CH4) on pilot-fuel ignition. The simulations reveal that CH4 has an effect on both stages of n-heptane autoignition: the small, first-stage, cool-flame-type, low-temperature ignition (LTI) and the larger, second-stage, high-temperature ignition (HTI). As the ratio of pilot-fuel to CH4 entrained into the spray decreases, the initial oxidization of CH4 consumes the OH radicals produced by pilot-fuel decomposition during LTI, thereby inhibiting its progression to HTI. Using imaging diagnostics, the spatial and temporal progression of LTI and HTI in DF combustion are measured in a heavy-duty optical engine, and the imaging data are analyzed to understand the cause of severe fluctuations in ignition timing and combustion completeness at low-load conditions. Images of cool-flame and hydroxyl radical (OH*) chemiluminescence serve as indicators of LTI and HTI, respectively. The cycle-to-cycle and spatial variation in ignition extracted from the imaging data are used as key metrics of comparison. The imaging data indicate that the local concentration of the pilot-fuel and the richness of the surrounding natural-gas air mixture are important for LTI and HTI, but in different ways. In particular, higher injection pressures and shorter injection durations increase the mixing rate, leading to lower concentrations of pilot-fuel more quickly, which can inhibit HTI even as LTI remains relatively robust. Decreasing the injection pressure from 80 MPa to 40 MPa and increasing the injection duration from 500 µs to 760 µs maintained constant pilot-fuel mass, while promoting robust transition from LTI to HTI by effectively slowing the mixing rate. This allows enough residence time for the OH radicals, produced by the two-stage ignition chemistry of the pilot-fuel, to accelerate the transition from LTI to HTI before being consumed by CH4 oxidation. Thus from a practical perspective, for a premixed natural gas fuel–air equivalence-ratio, it is possible to improve the “stability” of the combustion process by solely manipulating the pilot-fuel injection parameters while maintaining constant mass of injected pilot-fuel. This allows for tailoring mixing trajectories to offset changes in fuel ignition chemistry, so as to promote a robust transition from LTI to HTI by changing the balance between the local concentration of the pilot-fuel and richness of the premixed natural gas and air. This could prove to be a valuable tool for combustion design to improve fuel efficiency or reduce noise or perhaps even reduce heat-transfer losses by locating early combustion away from in-cylinder walls.

42 ENGINEERING↗