Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Windows”

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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Controls on reservoir properties in organic-matter-rich shales: Insights from MICP analysis

Mercury injection capillary pressure (MICP) analysis was used to study organic-matter-rich Devonian shales varying in maturity from marginally mature to postmature to discuss controls on drainage and imbibition in shale reservoirs. Six samples come from the New Albany Shale; their total organic carbon (TOC) ranged from 3.3–8.4 % and vitrinite reflectance (R o ) from 0.54–1.42 %. One Marcellus Shale sample with R o 2.50 % was used to extend the maturity range to the advanced dry gas window. Three coal samples of varying rank were also included for comparison. Porosity of the shales ranges from 1.5–5.0 %, and MICP-derived permeability ranges from 0.17–9.9 mD. Injection capillary pressure curves have a range of entry pressures from 0.055 to0.421 MPa, and no relationship of entry pressure with maturity was revealed. Maturity, however, has an influence on pore size distribution, with the higher-maturity samples having significantly lower volumes of pores with throats less than 10 nm in diameter. Withdrawal capillary pressure curves document a wide range of withdrawal efficiencies from 55 % to almost 100 %, and pores having throats between 3–50 nm in diameter play a major role in the ability of mercury to be released from the pore system. The obtained data provide valuable information about shale properties and their behavior not only in the air-mercury system but also under reservoir conditions.

02 PETROLEUM↗
DOE OSTI2021

Nucleon helicity generalized parton distribution at physical pion mass from lattice QCD

The generalized parton distributions (GPDs) offer a window on three-dimensional imaging of the nucleon, providing understanding of how the fundamental properties of the nucleon, such as its mass and spin, arise from the underlying quark and gluon degrees of freedom. In this work, we present the first lattice calculation of the nucleon isovector helicity GPD at physical pion mass, using an a≈0.09 fm lattice ensemble with 2+1+1 flavors of highly improved staggered quarks generated by MILC Collaboration. We perform the GPD calculation in Breit frame using averaged nucleon boost momentum P z ≈2.2 GeV with nonzero momentum transfers in [0.2,1.0] GeV 2 . Nonperturbative renormalization in RI/MOM scheme is used to obtain the quasi-distribution before matching to the lightcone GPDs. The three-dimensional distribution $\tilde{H}$(x, Q 2 ) is presented, along with the three-dimensional nucleon tomography and impact-parameter-dependent distribution for selected Bjorken x at μ=3 GeV in $\overline{MS}$ scheme.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Primordial black-hole dark matter via warm natural inflation

We report on a study of the natural warm inflationary paradigm (WNI). We show two important new results arise in this model. One is that the observational constraints on the primordial power spectrum from the cosmic microwave background (CMB) can be satisfied without going beyond the Planck scale of the effective field theory. The second is that WNI can inevitably provide perfect conditions for the production of primordial black holes (PBHs) in the golden window of black-hole mass range (10 -16 - 10 -11 M ⊙ ) where it can account for all of the dark matter content of the universe while satisfying observational constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Ab initio calculations of overlap integrals for μ → e conversion in nuclei

The rate for μ → e conversion in nuclei is set to provide the most stringent test of lepton-flavor symmetry and a window into physics beyond the Standard Model. However, to disentangle new lepton-flavor-violating interactions, in combination with information from μ → ey and μ → 3e, it is critical that uncertainties at each step of the analysis be controlled and fully quantified. In this regard, nuclear response functions related to the coupling to neutrons are notoriously problematic, since they are not directly constrained by experiment. We address these shortcomings by combining ab initio calculations with a recently improved determination of charge distributions from electron scattering by exploiting strong correlations among charge, point-proton, and point-neutron radii and densities. We present overlap integrals for 27 Al, 48 Ca, and 48 Ti including full covariance matrices, allowing, for the first time, for a comprehensive consideration of nuclear structure uncertainties in the interpretation of μ → e experiments.

ab initio calculations↗
DOE OSTI2021

Data trustworthiness signatures for nuclear reactor dynamics simulation

With the increased reliance on digitization in industrial control systems, the need for effective monitoring techniques has risen dramatically. Specifically, there is now a growing concern about the so-called false data injection (FDI) attacks. These attacks aim to alter the raw sensors’ data to cause malicious outcomes. Any serious FDI algorithm is based on an intimate knowledge of the system and its associated physics models, which renders conventional outlier/anomaly detection techniques almost obsolete in the face of such attacks. Thus, a critical need has emerged to develop a new class of defense methods that are capable of detecting FDI attacks under the assumption that the attacker has a strong familiarity with the system and its physics modeling. This class of defense methods are denoted by model-based defenses which are premised on the assumption that the attacker, while having a good understanding of the system, does not have full privileged access to all proprietary data and historical records of operation. However, (s)he is assumed to be capable of learning system behavior using self-learning techniques during an initial lie-in-wait period. To defend against this scenario, we propose a new model-based randomized window algorithm that searches time-series data for signatures that can serve as classifiers between normal and FDI scenarios. The classifiers are based on the correlations between the dominant degrees of freedom (DOFs) and the less-dominant DOFs (expected to be very sensitive to the system details that are unknown to the attacker). For demonstration, RELAP5 models are employed to calculate representative nuclear reactor behavior during a number of transient scenarios. Finally, falsified data are injected into the RELAP5-simulated behavior, and the proposed signature-identification algorithm is employed to detect the injected data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Passive heat removal in horizontally oriented micro-HTGRs

There are novel, horizontally oriented high-temperature gas-cooled micro-reactor (HTGR) designs under consideration because of their portability, simplicity, and reliable operation. These features of the micro-HTGR design can meet the fission battery attributes, such as economic, standardize, installed, unattended and reliable. Although there have been HTGR related safety studies, micro-HTGRs when horizontally oriented are expected to exhibit significantly different thermal physics. During the unavailability of helium circulation, the internal reactor core is designed to cool by block-to-block conduction and radiation, and the reactor vessel surface is cooled by the ambient air. This scenario is anticipated during the transport of the micro-HTGR in a shipping container. The conduction and radiation between the prismatic micro-HTGR blocks in the core can be influenced by variances in the thermal contacts. This work investigated the conduction within a simulated horizontal HTGR core. An experimental setup was used to validate a numerical model. The experimental setup consisted of a hexagonal assembly with scaled prismatic blocks placed within a high-temperature vacuum environment. The gaps between the blocks were well controlled and monitored. The experimental setup was designed in such a way that the temperature variation in the axial direction was minimal, such that the experiment could be observed as a 2D (r, ) heat transfer problem. The pressurized tube was equipped with Infra-Red (IR) transparent windows, and an IR camera was used to capture the spatio-temporal temperature evolution in the hexagonal block assembly during the cooldown experiments. The experimental scenario was computationally modeled with a finite element analysis (FEA) program. Once validated, the computational model was used to investigate the impact of gap conductance on overall decay heat removal. Using a conservative estimate for gap conductance value (100 W/m 2 -K) between the prismatic blocks, there is a negligible increase in temperature observed during decay heat generation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Insights into the emergence of mass from studies of pion and kaon structure

There are two mass generating mechanisms in the standard model of particle physics (SM). One is related to the Higgs boson and fairly well understood. The other is embedded in quantum chromodynamics (QCD), the SM’s strong interaction piece; and although responsible for emergence of the roughly 1 GeV mass scale that characterises the proton and hence all observable matter, the source and impacts of this emergent hadronic mass (EHM) remain puzzling. As bound states seeded by a valence-quark and -antiquark, pseudoscalar mesons present a simpler problem in quantum field theory than that associated with the nucleon. Consequently, there is a large array of robust predictions for pion and kaon properties whose empirical validation will provide a clear window onto many effects of both mass generating mechanisms and the constructive interference between them. This has now become significant because new-era experimental facilities, in operation, construction, or planning, are capable of conducting such tests and thereby contributing greatly to resolving the puzzles of EHM. These aspects of experiment, phenomenology, and theory, along with contemporary successes and challenges, are reviewed herein. In addition to providing an overview of the experimental status, we focus on recent progress made using continuum Schwinger function methods and lattice-regularised QCD. Further, advances made using other theoretical tools are also sketched. Our primary goal is to highlight the potential gains that can accrue from a coherent effort aimed at finally reaching an understanding of the character and structure of Nature’s Nambu–Goldstone modes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Theory of nuclear fission

Atomic nuclei are quantum many-body systems of protons and neutrons held together by strong nuclear forces. Under the proper conditions, nuclei can break into two (sometimes three) fragments which will subsequently decay by emitting particles. This phenomenon is called nuclear fission. Since different fission events may produce different fragmentations, the end-products of all fissions that occurred in a small chemical sample of matter comprise hundreds of different isotopes, including α particles, together with a large number of emitted neutrons, photons, electrons and antineutrinos. The extraordinary complexity of this process, which happens at length scales of the order of a femtometer, mostly takes less than a femtosecond but is not entirely over until all the lingering β decays have completed – which can take years – is a fascinating window into the physics of atomic nuclei. While fission may be more naturally known in the context of its technological applications, it also plays a crucial role in the synthesis of heavy elements in astrophysical environments. In both cases, simulations are needed for the many systems or energies inaccessible to experiments in the laboratory. In this context, the level of accuracy and precision required poses formidable challenges to nuclear theory. Overall, the goal of this article is to provide a comprehensive overview of the theoretical methods employed in the description of nuclear fission.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Recent progress in low energy neutrino scattering physics and its implications for the standard and beyond the standard model physics

Neutrinos continue to provide a testing ground for the structure of the standard model of particle physics as well as hints towards the physics beyond the standard model. Neutrinos of energies spanning over several orders of magnitude, originating in many terrestrial and astrophysical processes, have been detected via various decay and interaction mechanisms. At MeV scales, there has been one elusive process, until a few years ago, known as coherent elastic neutrino-nucleus scattering (CEvNS) that was theoretically predicted over five decades ago but was never observed experimentally. The recent experimental observation of the CEvNS process by the COHERENT collaboration at a stopped pion neutrino source has inspired physicists across many subfields. This has vital implications for nuclear physics, high-energy physics, astrophysics, and beyond. CEvNS, being a low-energy process, provides a natural window to study light, weakly-coupled, new physics in the neutrino sector. In this review, we intend to provide the current status of low energy neutrino scattering physics and its implications for the standard and beyond the standard model physics. We discuss the general formalism of calculating the tree-level CEvNS cross section and present estimated theoretical uncertainties on the CEvNS cross section stemming from different sources. We also discuss the inelastic scattering of tens of MeV neutrinos that have implications for supernova detection in future neutrino experiments. We discuss how the CEvNS experiments can be used as a testing ground for the Standard Model (SM) weak physics as well as in searching for the Beyond the Standard Model (BSM) physics signals. Any deviation from the SM predicted event rate either with a change in the total event rate or with a change in the shape of the recoil spectrum, could indicate new contributions to the interaction cross-section. The SM implications include the study of weak nuclear form factor and weak mixing angle. The BSM studies include non-standard interactions, neutrino electromagnetic properties, and sterile neutrino searches. In conclusion, stopped pion facilities are also a copious source of neutral and changed mesons that allow study of several dark sector physics scenarios such as vector portal models, leptophobic dark matter as well as axion-like particle searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Modern deep neural networks for Direct Normal Irradiance forecasting: A classification approach

The escalating energy demand and the adverse environmental impacts of fossil-fuel use necessitate a shift towards cleaner and renewable alternatives. Concentrated Solar Power (CSP) technology emerges as a promising solution, offering a carbon-free alternative for power generation. The efficiency and profitability of CSP depend on the Direct Normal Irradiance (DNI) component of solar radiation; hence, accurate DNI forecasting can help optimize CSP plants’ operations and performance. The unpredictable nature of weather phenomena, particularly cloud cover, introduces uncertainty into DNI projections. Existing DNI forecasting models use meteorological factors, which are both challenging to estimate numerically over short prediction windows and expensive to model through data at a sufficiently high spatial and temporal resolution. This research addresses the challenge by presenting a novel approach that formulates DNI prediction as a multi-class classification problem, departing from conventional regression-based methods. The primary objective of this classification framework is to identify optimal periods aligning with specific operational thresholds for CSP plants, contributing to enhanced dispatch optimization strategies. We model the DNI classification problem using four advanced deep neural networks – rectified linear unit (ReLU) networks, 1D residual networks (ResNets), bidirectional long short-term memory (BiLSTM) networks, and transformers – achieving accuracies up to 93.5% without requiring meteorological parameters.

14 SOLAR ENERGY↗
DOE OSTI2020

Diffusion and migration in polymer electrolytes

Mixtures of neutral polymers and lithium salts have the potential to serve as electrolytes in next-generation rechargeable Li-ion batteries. The purpose of this review is to expose the delicate interplay between polymer-salt interactions at the segmental level and macroscopic ion transport at the battery level. Since complete characterization of this interplay has only been completed in one system: mixtures of poly(ethylene oxide) and lithium bis(trifluoromethanesulfonyl)imide (PEO/LiTFSI), we focus on data obtained from this system. We begin with a discussion of the activity coefficient, followed by a discussion of six different diffusion coefficients: the Rouse motion of polymer segments is quantified by D seg , the self-diffusion of cations and anions is quantified by D self,+ and D self,- , and the build-up of concentration gradients in electrolytes under an applied potential is quantified by Stefan-Maxwell diffusion coefficients, D 0+ , D 0- , and D +- . The Stefan-Maxwell diffusion coefficients can be used to predict the velocities of the ions at very early times after an electric field is applied across the electrolyte. The surprising result is that D 0- is negative in certain concentration windows. A consequence of this finding is that at these concentrations, both cations and anions are predicted to migrate toward the positive electrode at early times. We describe the controversies that surround this result. Knowledge of the Stefan-Maxwell diffusion coefficients enable prediction of the limiting current. We argue that the limiting current is the most important characteristic of an electrolyte. Excellent agreement between theoretical and experimental limiting current is seen in PEO/LiTFSI mixtures. What sequence of monomers that, when polymerized, will lead to the highest limiting current remains an important unanswered question. It is our hope that the approach presented in this review will guide the development of such polymers.

25 ENERGY STORAGE↗
DOE OSTI2024

Confirming X-ray Parametric Down Conversion by Time-Energy Correlation

We present measurements of X-ray Parametric Down Conversion at the Advanced Photon Source synchrotron facility. Using an incoming pump beam at 22 keV, we observe the simultaneous, elastic emission of down-converted photon pairs generated in a diamond crystal. The pairs are detected using high count rate silicon drift detectors with low noise. Production by down-conversion is confirmed by measuring time-energy correlations in the detector signal, where photon pairs within an energy window ranging from 10 to 12 keV are only observed at short time differences. By systematically varying the crystal misalignment and detector positions, we obtain results that are consistent with the constant total of the down-converted signal. Our maximum rate of observed pairs was 130 /hour, corresponding to a conversion efficiency for the down-conversion process of 5.3±0.5×10 -13 .

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Harmonizing solar induced fluorescence across spatial scales, instruments, and extraction methods using proximal and airborne remote sensing: A multi-scale study in a soybean field

Solar-induced chlorophyll fluorescence (SIF) has been widely used to track vegetation photosynthesis at different scales ranging from in-situ measurements to satellite products. Airborne platforms sample SIF data at a spatial scale intermediate between in-situ and satellite, matching that of ground measurement (e.g. flux tower footprints and other field sampling), enabling us to explore causes of SIF variation and validate satellite-based SIF products. However, harmonizing SIF across sensors and platforms (correcting for systematic errors to yield a consistent, comparable SIF product) is challenging because SIF can be retrieved in different absorption windows, with different instruments and methods complicating the comparison between different observational levels (i.e., ground, airborne, satellites) and between sites equipped with different instruments with varying optical properties (spectral resolution and sampling intervals, spatial resolution). Additionally, the spatial and temporal variability of atmospheric properties can influence the retrieval of the weak SIF signal. Because of these complications, direct comparisons of airborne and ground SIF across scales are rarely attempted. Here, in this study, we combined airborne SIF data with simultaneous ‘ground truth’ data collected by stationary and mobile platforms in a soybean field in Nebraska, USA. In this effort, we tested several SIF extraction methods, including Fraunhofer Line Discrimination (FLD), improved Fraunhofer Line Discrimination (iFLD), Spectral Fitting Method (SFM), SpecFit, and a Singular Vector Decomposition (SVD) method. The SpecFit method was sensitive to the 715–740 nm water bands and removing the water bands in the fitting process yielded better agreement between the airborne and ground SIF spectra. Accurate estimation of the ground level downwelling irradiance obtained by ground measurements over a calibration target improved agreement between airborne and ground SIF retrievals at the O 2 A band, and allowed us to derive a SIF dataset with improved agreement across platforms and sampling scales. This experimental approach provided a method for generating comparable SIF signals across instruments, methods and platforms, which is critical to understanding the SIF-GPP relationship at different scales and to cross-validate the diversity of platforms used for satellite products calibration and validation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Power generation forecasting for solar plants based on Dynamic Bayesian networks by fusing multi-source information

A Dynamic Bayesian network (DBN) model for solar power generation forecasting in solar plants is proposed in this paper. The key idea is to fuse sensor data, operational indicators, meteorological data, lagged output power information, and model errors for more accurate short-term (e.g., hours) and mid-term (e.g., days to weeks) power generation forecasting. The proposed DBN augments automated data-driven structure learning with expert knowledge encoding using continuous and categorical data given constraints to represent causal relationships within a solar inverter system. Additionally, an error compensation mechanism is proposed to capture temporal fluctuation. The effectiveness of the DBN on solar power generation forecasting was evaluated by rolling window analysis with one-year testing data collected from a local solar plant. The proposed DBN is compared with four state-of-art methods including support-vector regression (SVR), k-nearest neighbors (kNN), artificial neural network (ANN), and long short-term memory (LSTM) models. The result show that the proposed DBN achieves better accuracy in general, and it is not as data-hungry as some neural network-based models. The proposed DBN is also shown to have robust and consistent forecasting power with different forecasting horizons. The accuracy is 92% - 95% from one hour to one week ahead forecasting.

14 SOLAR ENERGY↗
DOE OSTI2021

Analytical characterization of laser induced plasmas towards uranium isotopic analysis in gaseous uranium hexafluoride

To perform direct enrichment assay on gaseous uranium hexafluoride (UF 6 ) with laser induced breakdown spectroscopy (LIBS), the dominant spectral-line features, evolution of the signal and background of the U II 424.437 nm line, and its Stark width and shift, were studied as a function of UF 6 gas pressure and pulse energy of a nanosecond Nd:YAG laser. In this work, vapor pressure of UF 6 was found to be the most important parameter for LIBS analysis of gaseous UF 6 . Spectral congestion with numerous U lines of high excitation potential was observed and signal-to-background ratio (SBR) was low for measurements with 80 Torr UF 6 . Only when both UF 6 vapor pressure and laser pulse energy were low, for example, less than 20 Torr pressure and 30 mJ pulse energy, the resultant LIBS spectra from gaseous UF 6 resembled those obtained from solid U samples. The experimental data also suggest that U and F atoms recombine back to UF 6 after the laser pulse. The U emission was found to decay fast with a persistent background signal, degrading SBR with delay time. Systematic positive biases were found for UF 6 enrichment assays performed with the 235 U– 238 U line pair at 424.412–424.437 nm, which was confirmed to be caused by self-absorption. Even with optimization of experimental parameters and incorporation of a self-absorption term into the spectral-fitting algorithm, to reduce and compensate for self-absorption, self-absorption is still a main factor limiting accurate UF 6 enrichment assay. The use of another spectral window which contains no resonance lines is a prospective solution for the self-absorption issue.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Soil organic carbon accumulation rates on Mediterranean abandoned agricultural lands

Secondary succession on abandoned agricultural lands can produce climate change mitigation co-benefits, such as soil carbon sequestration. However, the accumulation of soil organic carbon (SOC) in Mediterranean regions has been difficult to predict and is subject to multiple environmental and land management factors. Gains, losses, and no significant changes have all been reported. Here we compile chronosequence data (n = 113) from published studies and new field sites to assess the response of SOC to agricultural land abandonment in peninsular Spain. In this work we found an overall SOC accumulation rate of +2.3% yr -1 post-abandonment. SOC dynamics are highly variable and context-dependent. Minimal change occurs on abandoned cereal croplands compared to abandoned woody croplands (+4% yr -1 ). Accumulation is most prevalent within a Goldilocks climatic window of ~13–17 °C and ~450–900 mm precipitation, promoting >100% gains after three decades. Our secondary forest field sites accrued 40.8 Mg C ha -1 (+172%) following abandonment and displayed greater SOC and N depth heterogeneity than natural forests demonstrating the long-lasting impact of agriculture. Although changes in regional climate and crop types abandoned will impact future carbon sequestration, abandonment remains a low-cost, long-term natural climate solution best incorporated in tandem with other multipurpose sustainable land management strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Nanotwin formation in Ni-Mo-W alloys deposited by dc magnetron sputtering

Nanotwinned metals and alloys have an attractive suite of properties, but the formation of the underlying nanostructure is generally dependent on the alloy chemistry and processing conditions. This study was undertaken to investigate the effect of deposition rate on nanotwin formation in sputter deposited Ni 84 Mo 11 W 5 that possess ultrahigh strength and stability. Specifically, deposition rates of 0.5-2.3 nm/s were examined and the grain size, texture, twin spacing and hardness were characterized. Minimal variations in the underlying nanostructure and attendant hardness were observed, elucidating a wide processing window and the importance of chemistry on the formation of nanotwins in this alloy.

36 MATERIALS SCIENCE↗