Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Exponential distribution”

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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Greenhouse Gas Concentration Data Recovery Algorithm for a Low Cost, Laser Heterodyne Radiometer

The goal of a coordinated effort between groups at GWU and NASA GSFC is the development of a low-cost, global, surface instrument network that continuously monitors three key carbon cycle gases in the atmospheric column: carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), as well as oxygen (O2) for atmospheric pressure profiles. The network will implement a low-cost, miniaturized, laser heterodyne radiometer (mini-LHR) that has recently been developed at NASA Goddard Space Flight Center. This mini-LHR is designed to operate in tandem with the passive aerosol sensor currently used in AERONET (a well established network of more than 450 ground aerosol monitoring instruments worldwide), and could be rapidly deployed into this established global network. Laser heterodyne radiometry is a well-established technique for detecting weak signals that was adapted from radio receiver technology. Here, a weak light signal, that has undergone absorption by atmospheric components, is mixed with light from a distributed feedback (DFB) telecommunications laser on a single-mode optical fiber. The RF component of the signal is detected on a fast photoreceiver. Scanning the laser through an absorption feature in the infrared, results in a scanned heterodyne signal io the RF. Deconvolution of this signal through the retrieval algorithm allows for the extraction of altitude contributions to the column signal. The retrieval algorithm is based on a spectral simulation program, SpecSyn, developed at GWU for high-resolution infrared spectroscopies. Variations io pressure, temperature, composition, and refractive index through the atmosphere; that are all functions of latitude, longitude, time of day, altitude, etc.; are modeled using algorithms developed in the MODTRAN program developed in part by the US Air Force Research Laboratory. In these calculations the atmosphere is modeled as a series of spherically symmetric shells with boundaries specified at defined altitudes. Temperature, pressure, and species mixing ratios are defined at these boundaries. Between the boundaries, temperature is assumed to vary linearly with altitude while pressure (and thus gas density) vary exponentially. The observed spectrum at the LHR instrument will be the integration of the contributions along this light path. For any absorption measurement the signal at a particular spectral frequency is a linear combination of spectral line contributions from several species. For each species that might absorb in a spectral region, we have pre-calculated its contribution as a function of temperature and pressure. The integrated path absorption spectrum can then by calculated using the initial sun angle (from location, date, and time) and assumptions about pressure and temperature profiles from an atmospheric model. The modeled spectrum is iterated to match the experimental observation using standard multilinear regression techniques. In addition to the layer concentrations, the numerical technique also provides uncertainty estimates for these quantities as well as dependencies on assumptions inherent in the atmospheric models.

Miller, J. Houston↗
DOE OSTI2026

Characterization of core neutrals using passive measurements of the D α spectrum near the X -point in the DIII-D tokamak

New spectroscopic measurements of deuterium Balmer-α emission are used to infer the spatial distribution of neutral particles near the X-point in a diverted high confinement mode plasma. The charge exchange neutral spectroscopy (CENS) diagnostic—recently installed on the DIII-D tokamak—uses 15 lines of sight extending from the edge of the confined region (ρ ≈ 0.7) to the X-point in lower single-null plasmas. Each CENS line of sight is spectrally resolved around the deuterium Balmer-α wavelength (6561 Å) to measure the Doppler shift, line broadening, and intensity of Dα emission. Thermal line broadening is used to identify emission from neutrals undergoing charge-exchange (CX) with high temperature ions in the confined plasma. This spectral information allows a more accurate determination of the neutral density deeper inside the confined plasma compared to traditional filter-based diagnostics. We present two methods of analyzing CENS measurements: (1) fitting the spectrum from each view-chord separately, and (2) a tomographic method for inverting the neutral density over a 2D region of space using all CENS views collectively. The neutral density profile is found to decay exponentially in the radial direction with two scale-lengths. In the pedestal region the neutral density decays at a rate approximately equal to the local mean-free-path for CX collisions, $L_{n_\mathrm{D0}}\approx \lambda_\text{CX}$. Further inside the plasma the neutral density decays at a rate equal to the mean-free-path for ionization, $L_{n_\mathrm{D0}}\approx \lambda_\text{inz.}$. The separatrix $n_\mathrm{D0}$ value is found to be approximately $2\times10^{15}$ m−3. Based on results from the 2D inversion, the density of neutrals is found to increase along the separatrix approaching the X-point by a factor of $\approx 5\times$ over the region covered by the CENS diagnostic.

X-point neutrals↗
DOE OSTI2024

Pyrolysis of high-density polyethylene: Degradation behaviors, kinetics, and product characteristics

Pyrolysis is a promising technology for converting plastic waste into valuable raw materials while offering a potential solution to the global plastic pollution crisis. In this study, the thermal pyrolysis of high-density polyethylene (HDPE) is investigated in a drop tube reactor under nearly isothermal conditions. The impact of reaction temperature and gas/volatile residence time on carbon conversion and product distribution is examined across a range of 500–900°C and 3.6–32.2s, respectively. Non-condensable gas products detected by online mass spectrometry are H 2 , CH 4 , C 2 H 4 , C 2 H 6 , C 3 H 6 , and C 3 H 8 . At elevated temperatures and prolonged residence time, H 2 yield reaches as high as 8.6 wt% of the initial HDPE mass due to intensified cracking reactions of C 2 –C 3 hydrocarbons and long-chain aliphatic compounds. Consequently, pyrolysis tars consist mainly of polycyclic aromatic hydrocarbons (PAHs) with 5–7 rings, accompanied by visible coke deposition within the reactor. HDPE decomposition to volatiles is an endothermic process and it is complete at a temperature between 492°C and 525°C, depending on the heating rate employed, from non-isothermal thermogravimetric analysis and differential scanning calorimetry (TGA-DSC) measurements. The thermal degradation of HDPE pellets follows the two-dimensional nucleation growth model for conversion levels up to 0.8 with an apparent activation energy of 259–270 kJ/mol and a pre-exponential factor of 4.83 × 10 17 –1.37 × 10 19 min -1 , determined from various isoconversional methods such as Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), and Starink, along with Criado's master plots. Further, these findings provide valuable insights into optimizing process parameters and refining reactor design for pyrolysis, which can be integrated with gasification and reforming processes to enhance hydrogen production on a larger scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

Control Design Strategies to Enhance Long-Term Aircraft Structural Integrity

Over the operational lifetime of both military and civil aircraft, structural components are exposed to hundreds of thousands of low-stress repetitive load cycles and less frequent but higher-stress transient loads originating from maneuvering flight and atmospheric gusts. Micro-material imperfections in the structure, such as cracks and debonded laminates, expand and grow in this environment, reducing the structural integrity and shortening the life of the airframe. Extreme costs associated with refurbishment of critical load-bearing structural components in a large fleet, or altogether reinventoring the fleet with newer models, indicate alternative solutions for life extension of the airframe structure are highly desirable. Increased levels of operational safety and reliability are also important factors influencing the desirability of such solutions. One area having significant potential for impacting crack growth/fatigue damage reduction and structural life extension is flight control. To modify the airframe response dynamics arising from command inputs and gust disturbances, feedback loops are routinely applied to vehicles. A dexterous flight control system architecture senses key vehicle motions and generates critical forces/moments at multiple points distributed throughout the airframe to elicit the desired motion characteristics. In principle, these same control loops can be utilized to influence the level of exposure to harmful loads during flight on structural components. Project objectives are to investigate and/or assess the leverage control has on reducing fatigue damage and enhancing long-term structural integrity, without degrading attitude control and trajectory guidance performance levels. In particular, efforts have focused on the effects inner loop control parameters and architectures have on fatigue damage rate. To complete this research, an actively controlled flexible aircraft model and a new state space modeling procedure for crack growth have been utilized. Analysis of the analytical state space model for crack growth revealed the critical mathematical factors, and hence the physical mechanism they represent, that influenced high rates of airframe crack growth. The crack model was then exercised with simple load inputs to uncover and expose key crack growth behavior. To characterize crack growth behavior, both "short-term" laboratory specimen test type inputs and "long-term" operational flight type inputs were considered. Harmonic loading with a single overload revealed typical exponential crack growth behavior until the overload application, after which time the crack growth was retarded for a period of time depending on the overload strength. An optimum overload strength was identified which leads to maximum retardation of crack growth. Harmonic loading with a repeated overload of varying strength and frequency again revealed an optimum overload trait for maximizing growth retardation. The optimum overload strength ratio lies near the range of 2 to 3 with dependency on frequency. Experimental data was found to correlate well with the analytical predictions.

Newman, Brett A.↗
NASA NTRSDate not supplied

Image-to-Image Wildfire Detection via Quantum-Compatible Variational Segmentation from Remotely-sensed Data

Over the last decade, the incidence of wildfires has surged, causing widespread destruction globally. To better comprehend and manage these incidents, remote sensing and aerial missions have been implemented in recent efforts. However, this has resulted in an exponential rise in the amount of remote sensing data utilization, leading to a need for intelligent automation of data extraction in wildfire studies. Machine learning provides an accurate automated approach for detecting these natural anomalies and facilitates decision-makers to take prompt actions. To make insightful decisions in wildfire management, it is imperative to move beyond simple detection and explore the potential of probabilistic generative machine learning for creating "what-if" scenarios for various wildfire conditions. Such models offer improved representation of the stochastic nature of wildfire events. However, the optimization of these models can be computationally expensive, especially when using classical computers. Quantum computers have recently emerged as a promising solution to reduce the computational cost of training such models and improve their performance. In this study, we aim to utilize quantum-compatible machine learning techniques to implement our probabilistic generative approach. To that end, we propose a supervised probabilistic variational model consisting of a U-NET-based image-to-image component along with encoder and decoder networks which work as a variational autoencoder (VAE) component. Additionally, we explore the type of latent distribution type in the VAE component and implement different means for modeling the prior distribution. We further investigate the quantum-compatible versions of the model compared to the classical counterpart and benchmark potential benefits of quantum compatibility over the classical model.

quantum machine learning↗
DOE OSTI2022

Using a Grid-Forming Inverter to Stabilize a Low-Inertia Power System - Maui Hawaiian Island

As power systems around the world integrate greater amounts of wind and solar photovoltaic power, periods of very high instantaneous power shares of inverters, the primary interfacing technology for these generation sources, are complicating system stability and control. The contemporary, primary mode of inverter operation, grid-following, which explicitly assumes the presence of a local, stable voltage waveform, yields operational inadequacy at high instantaneous power shares potentially leading to instability due to the low-inertia conditions, as well as the correlated reduced voltage forming capacity on the respective system. Parallel connected grid-forming inverters, which directly regulate the local voltage, are a solution that is expected to bolster system stability and mitigate the shortcomings of the grid-following technology. In this paper, grid-following and two types of grid-forming inverter control, the traditional linear droop and the recently introduced nonlinear exponential droop (Droop-e), are simulated on a low-inertia, H = 0.48s, high inverter-based resource scenario, 97%, with a validated electromagentic transient domain model of the Hawaiian island of Maui power system. The benefit of a single grid-forming device over its grid-following counterpart is significant, both in terms frequency deviation and voltage stability. Further, the superiority of the Droop-e and the associated secondary power sharing control over both grid-following and linear droop grid-forming technologies is displayed, with improved nadir and rate of change of frequency over the linear droop control.

droop control↗
DOE OSTI2026

Engineering Clostridium Tyrobutyricum for High Butanol Production through Induction Expression of Exogenous NADPH-Dependent HBD

Clostridium tyrobutyricum Δ cat 1:: adh E2 is a promising cell factory for butanol production because of its robustness, high butanol tolerance, and minimal butyrate production. However, excessive acetate and ethanol production remains a major bottleneck limiting its butanol yield. Coexpressing an exogenous hbd ( Ck ) encoding the NADPH-dependent 3-hydroxybutyryl-CoA dehydrogenase (HBD) from Clostridium kluyveri with adh E2 could increase the C4 carbon flux, resulting in increased butanol and decreased acetate and ethanol production. However, constitutively overexpressing hbd ( Ck ) in Δ cat 1:: adh E2 shows little improvement in butanol yield, productivity, and selectivity, which might be caused by redox imbalance and growth inhibition. To alleviate this problem, C. tyrobutyricum MΔ cat 1:: adh E2- Pbgal-hbd ( Ck ) with a dynamic expression of hbd ( Ck ) controlled by an inducible promoter was developed. In serum bottle fermentation at 37 °C, when the hbd ( Ck ) expression was induced at 12 h or in the early exponential phase, butanol production increased ∼20% in yield (from 0.22 to 0.27 g/g glucose), 87.5% in productivity (from 0.16 to 0.30 g/L·h), and 52% in selectivity (from 0.46 to 0.70 g/g total products) compared to the control strain without expressing any hbd(Ck), whereas hbd ( Ck ) expression induced at 0 or 24 h in MΔ cat 1:: adh E2-P bgal - hbd ( Ck ) or constitutively in MΔ cat 1:: adh E2-P cat 1- hbd ( Ck ) showed significantly lower butanol yield and productivity. At 25 °C, MΔ cat 1:: adh E2-P bgal - hbd ( Ck ) with 12 h induction produced the highest butanol titer of 23 g/L with 0.32 g/g yield, 0.16 g/L·h productivity, and 0.83 g/g product selectivity due to much reduced acetate formation. Subsequent scale-up to a stirred-tank bioreactor at 37 °C increased productivity to 0.39 g/L·h while also achieving high butanol titer (21.8 g/L), yield (0.30 g/g), and selectivity (0.67 g/g). The optimized induction timing resulted in a balanced NAD(P)H pool, effectively channeling substrates toward butanol biosynthesis. It was concluded that the timing for hbd ( Ck ) expression was critical as it affected glucose catabolism, cell growth, redox balance, and carbon flux distribution. These findings underscore the potential of dynamic metabolic regulation to overcome bottlenecks in biobutanol production, providing a scalable and economically viable bioprocess for industrial application.

Clostridium tyrobutyricum↗
NASA NTRS2023

Ocean Carbon From Space: Current Status and Priorities for the Next Decade

The ocean plays a central role in modulating the Earth’s carbon cycle. Monitoring how the ocean carbon cycle is changing is fundamental to managing climate change. Satellite remote sensing is currently our best tool for viewing the ocean surface globally and systematically, at high spatial and temporal resolutions, and the past few decades have seen an exponential growth in studies utilising satellite data for ocean carbon research. Satellite-based observations must be combined with in-situ observations and models, to obtain a comprehensive view of ocean carbon pools and fluxes. To help prioritise future research in this area, a workshop was organised that assembled leading experts working on the topic, from around the world, including remote-sensing scientists, field scientists and modellers, with the goal to articulate a collective view of the current status of ocean carbon research, identify gaps in knowledge, and formulate a scientific roadmap for the next decade, with an emphasis on evaluating where satellite remote sensing may contribute. A total of 449 scientists and stakeholders participated (with balanced gender representation), from North and South America, Europe, Asia, Africa, and Oceania. Sessions targeted both inorganic and organic pools of carbon in the ocean, in both dissolved and particulate form, as well as major fluxes of carbon between reservoirs (e.g., primary production) and at interfaces (e.g., air-sea and land–ocean). Extreme events, blue carbon and carbon budgeting were also key topics discussed. Emerging priorities identified include: expanding the networks and quality of in-situ observations; improved satellite retrievals; improved uncertainty quantification; improved understanding of vertical distributions; integration with models; improved techniques to bridge spatial and temporal scales of the different data sources; and improved fundamental understanding of the ocean carbon cycle, and of the interactions among pools of carbon and light. We also report on priorities for the specific pools and fluxes studied, and highlight issues and concerns that arose during discussions, such as the need to consider the environmental impact of satellites or space activities; the role satellites can play in monitoring ocean carbon dioxide removal approaches; economic valuation of the satellite based information; to consider how satellites can contribute to monitoring cycles of other important climatically-relevant compounds and elements; to promote diversity and inclusivity in ocean carbon research; to bring together communities working on different aspects of planetary carbon; maximising use of international bodies; to follow an open science approach; to explore new and innovative ways to remotely monitor ocean carbon; and to harness quantum computing. Overall, this paper provides a comprehensive scientific roadmap for the next decade on how satellite remote sensing could help monitor the ocean carbon cycle, and its links to the other domains, such as terrestrial and atmosphere.

oceanography↗
NASA NTRS2016

Results of Outdoor to Indoor Propagation Measurements from 5-32GHz

The demand for wireless services has increased exponentially in the last few years and shows no signs of slowing in the near future. In order for the next generation wireless to provide seamless access, whether the user is indoors or out, a thorough understanding and validation of models describing the impact of building entry loss (BEL) is required. This information is currently lacking and presents a challenge for most system designers. For this reason empirical data is needed to assess the impact of BEL at frequencies that are being explored for future mobile broadband applications This paper present the results of measurements of outdoor-to-indoor propagation from 5-32 GHz in three different buildings. The first is a newer building that is similar in construction to modern residential home. The second is an older commercial office building. The last building is a very new commercial office building built using modern green building techniques. These three buildings allow for the measurement of propagation losses through both modern and older materials; such as glass windows and exterior block and siding. Initial results found that at particular spatial locations the BEL could be less than 1dB or more than 70dB with free space losses discounted (this is likely influenced by multipath). Additionally, it was observed that the PDF distributions of a majority of the measurements trended toward log-normal with means and standard deviations ranging from 8-38dB and 6-14dB, respectively.

building entry loss↗
NASA NTRS1994

The RSA survey of dwarf galaxies, 1: Optical photometry

We present detailed surface photometry, based on broad B-band charge coupled device (CCD) images, of about 80 dwarf galaxies. Our sample represents approximately 10% of all dwarf galaxies identified in the vicinity of Revised Shapley-Ames (RSA) galaxies on high resolution blue photographic plates, referred to as the RSA survey of dwarf galaxies. We derive global properties and radial surface brightness profiles, and examine the morphologies. The radial surface brightness profiles of dwarf galaxies, whether early or late type, display the same varieties in shape and complexity as those of classical giant galaxies. Only a few are well described by a pure r(exp 1/4) law. Exponential profiles prevail. Features typical of giant disk galaxies, such as exponential profiles with a central depression, lenses, and even, in one case (IC 2041), a relatively prominent bulge are also found in dwarf galaxies. Our data suggest that the central region evolves from being bulge-like, with an r(exp 1/4) law profile, in bright galaxies to a lens-like structure in dwarf galaxies. We prove detailed surface photometry to be a helpful if not always sufficient tool in investigating the structure of dwarf galaxies. In many cases kinematic information is needed to complete the picture. We find the shapes of the surface brightness profiles to be loosely associated with morphological type. Our sample contains several new galaxies with properties intermediate between those of giant and dwarf ellipticals (but no M32-like objects). This shows that such intermediate galaxies exist so that at least a fraction of early-type dwarf ellipticals is structurally related to early-type giants instead of belonging to a totally unrelated, disjunct family. This supports an origin of early-type dwarf galaxies as originally more massive systems that acquired their current morphology as a result of substantial, presumable supernova-driven, mass loss. On the other hand, several early-type dwarfs in our sample are merger candidates. Merger events may lead to anisotropic velocity distributions in systems of any luminosity, including dwarfs. The RSA sample of dwarf galaxies is more likely to contain mergers because, in contrast to earlier dwarf galaxy surveys that have focused on clusters and rich groups of galaxies, the RSA dwarfs are typically located in low density environments. The occurrence of mergers among dwarf galaxies is of interest in connection with the rapid evolution of faint blue galaxy counts at redshift z less than 1 which suggests that dwarf galaxies were about five times more numerous in the recent past. Finally, our sample contains several examples of late-type dwarfs and 'transition' types that are potential precursors of nucleated early-type dwarfs. All the above processes--mass loss, mergers, astration--are likely to have contributed to the formation of the current population of diffuse early-type dwarfs. A few new redshifts of dwarf galaxies are reported in this paper.

Vader, J. Patricia↗
DOE OSTI2025

National serosurvey and risk mapping reveal widespread distribution of Coxiella burnetii in Kenya

Coxiella burnetii, the causative agent of Q fever, is an emerging pathogen that has the potential to cause severe chronic infections in animals and humans worldwide. The detrimental impact on public health is projected to be higher in the low- and middle-income countries given their lower capacity to sustain effective surveillance and response measures. We implemented a national serosurvey of cattle in Kenya to map the spatial distribution of the pathogen. The study used serum samples that were collected from randomly selected cattle in different ago-ecological zones across the country. These samples were screened for the pathogen using PrioCHECK Ruminant Q Fever AB Plate ELISA kit. The laboratory findings were analyzed using INLA package to identify risk factors for C. burnetii exposure from herd- and animal-level factors, area, and bioclimatic datasets accessed from online databases. A total of 6,593 cattle were recruited for the study; of these, 7.9% (95% CI; 7.2–8.5) were seropositive. Outputs from the multivariable analysis revealed that the animal age and some of the geographical variables including wind speed, area under shrubs and “petric calcisols” type of soil were significantly associated with C. burnetii seropositivity. Being a calf, weaner or subadult was associated with lower odds of exposure compared to being an adult by 0.24 (credibility interval: 2.5% and 97.5%), 0.41 (0.30–0.55) and 0.51 (0.38–0.69), respectively. In addition, a unit increase in the wind speed increased the odds of C. burnetii seropositivity by 1.27 (1.05–1.52) while an increase on the land area under shrubs was associated with lower odds of exposure (0.67 [0.47–0.69]). The effect of petric calcisols was non-linear; an increase of the land area with this soil type was associated with an exponential increase in C. burnetii seropositivity. This study provides new data on C. burnetii seroprevalence, information of its risk factors and a prevalence map that can be used for C. burnetii risk surveillance and control. The identification of environmental risk factors for C. burnetii exposure, and the increasing awareness of the zoonotic potential of the pathogen, calls for the need to enhance the existing collaborations for the surveillance and control of C. burnetii in line with the One Health framework. The evidence generated on the potential role of environmental factors can also be used to design nature-based interventions, such as replacement of vegetation in denuded areas, to reduce potential for the aerosolization of the pathogen. Livestock vaccination in the hotspots would also reduce animal infections and hence the contamination of the environment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker–Planck Equations

The Fokker-Planck (FP) equation is a foundational partial differential equation (PDE) in stochastic processes involving Brownian motions. However, the curse of dimensionality (CoD) poses a formidable challenge when dealing with high-dimensional FP equations. Although Monte Carlo simulation and (vanilla) Physics-Informed Neural Networks (PINNs) have shown the potential to tackle CoD, both methods exhibit significant numerical errors in high dimensions when dealing with the probability density function (PDF) associated with Brownian motion. The point-wise PDF values tend to decrease exponentially as dimensionality increases, surpassing the precision of numerical simulations and resulting in substantial errors. In addition, due to its massive sampling, Monte Carlo fails to offer fast sampling. Modeling the logarithm likelihood (LL) via vanilla PINNs transforms the FP equation into a notoriously difficult Hamilton-Jacobi-Bellman (HJB) equation, which is impractical for PINN learning, whose error grows rapidly with dimension. To this end, we propose a novel approach utilizing a score-based solver to fit the score function in stochastic differential equations (SDEs). The score function, defined as the gradient of the LL, plays a fundamental role in inferring LL and PDF and enables fast SDE sampling, offering an effective means to overcome the CoD. Three fitting methods, Score Matching (SM), Sliced Score Matching (SSM), and Score-PINN, are introduced, each contributing unique advantages in computational complexity, accuracy, and generality. The proposed score-based SDE solver operates in two stages: first, employing score matching or Score-PINN to acquire the score function; and second, solving the LL via an ordinary differential equation (ODE) using the obtained score function. Comparative evaluations across these methods showcase varying trade-offs. The proposed methodology is evaluated across diverse SDEs, including anisotropic Ornstein-Uhlenbeck processes, geometric Brownian motion, and Brownian motion with varying eigenspace. We also test various distributions, including Gaussian, Log-normal, Laplace, and Cauchy distributions. The numerical results demonstrate the score-based SDE solver’s stability, speed, and performance across different experimental settings, solidifying its potential as a solution to CoD for high-dimensional FP equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Ground-state properties of light 4 n self-conjugate nuclei in ab initio no-core Monte Carlo shell model calculations with nonlocal N N interactions

We report J π = 0 + ground-state energies and point-proton radii of 4 He, 8 Be, 12 C, 16 O, and 20 Ne nuclei calculated by the ab initio no-core Monte Carlo shell model with the JISP16 and Daejeon16 nonlocal NN interactions. Ground-state energies are obtained in the basis spaces up to seven oscillator shells (N shell =7) with several oscillator energies (ℏω) around the optimal oscillator energy for the convergence of ground-state energies. These energy eigenvalues are extrapolated to obtain estimates of converged ground-state energies in each basis space using energy variances of computed energy eigenvalues. We further extrapolate these energy-variance-extrapolated energies obtained in the finite basis spaces to infinite basis-space results with an empirical exponential form. This form features a dependence on the basis-space size but is independent of the value of ℏω used for the harmonic-oscillator basis functions. Point-proton radii for these states of atomic nuclei are also calculated following techniques employed for the energies. From these results, it is found that the Daejeon16 NN interaction provides good agreement with experimental data up to approximately 16 O, while the JISP16 NN interaction provides good agreement with experimental data up to approximately 12 C. Beyond these nuclei, the interactions produce overbinding accompanied by radii that are too small. These findings suggest and encourage further revisions of nonlocal NN interactions towards the investigation of nuclear structure in heavier-mass regions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Navigating Integration: Key Challenges for Data Centers, Nuclear Stakeholders, and Utility Operators

he exponential growth of data centers—driven by artificial intelligence and cloud computing—is reshaping the U.S. energy landscape, presenting urgent challenges and transformative opportunities for data center developers, nuclear energy providers, and utility operators. As data centers are projected to consume up to 12% of U.S. electricity by 2028, stakeholders must address rapid deployment needs, grid congestion, and the demand for reliable, high-quality power. This presentation explores the multifaceted barriers to integrating data centers with nuclear and utility infrastructure, including land use constraints, public perception, regulatory complexity, and workforce alignment. It highlights the distinct priorities and operational cultures of each sector, and the friction that arises from misaligned planning horizons and risk tolerances. We examine collaborative strategies such as co-siting, hybrid power-purchase agreements, unified community engagement, and innovative financing models.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Use of a Mylar filter to eliminate vacuum ultraviolet pulse pileup in low-energy x-ray measurements

We describe a method to reduce vacuum ultraviolet (VUV) pulse pileup (PPU) in x-ray pulse-height Silicon Drift Detector (SDD) signals. An Amptek FAST SDD, with C1 (Si 3 N 4 ) window, measures bremsstrahlung emitted from PFRC-2 plasma to extract the electron temperature (T e ) and density (n e ). The C1 window has low transmissivity for photons with energy below 200 eV though will transmit some VUV and soft x-ray photons, which PFRC-2 plasmas abundantly emit. Multi-VUV-photon PPU contaminates the interpretation of x rays with energy > 100 eV, particularly in a low-energy exponential tail. The predicted low transmissivity of ~1 μm thick Mylar [polyethylene terephthalate (PET)] to photons of energy <100 eV led to the selection of Mylar as the candidate filter to reduce VUV PPU. Experiments were conducted on an x-ray tube with a graphite target and on a quasi-Maxwellian tenuous plasma (n e ~ 10 9 cm –3 ) with effective temperatures reaching 1500 eV. A Mylar filter thickness of 850 nm is consistent with the results. The Mylar-filter-equipped SDD was then used on the PFRC-2 plasma, showing a substantial reduction in the low-energy x-ray signal, supporting our hypothesis of the importance of VUV PPU. Here, we describe the modeling and experiments performed to characterize the effect of the Mylar filter on SDD measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Evolving efforts to maintain and improve XPS analysis quality in an era of increasingly diverse uses and users

Based on literature analysis, X-ray photoelectron spectroscopy (XPS) use continues to increase exponentially. This increased use is accompanied by anecdotal reports and systematic analyses indicating a growing presence of significantly flawed data analyses. Recognition of this problem within the surface analysis community has increased with an understanding that both inexperienced users and increased use of XPS outside the surface analysis community contribute to the problem. The XPS community has initiated several efforts to help address the problem, which is not unique to XPS. This paper describes some of the specific problems identified and some of the community efforts intended to address them. Here, we describe activities focused on three specific issues: (i) requests for detailed guides and protocols and bite-sized versions of information for non-experts, (ii) incomplete data and analysis reporting, and (iii) the high rate of peak fitting problems. A 2019 survey identified the need for guides, protocols, and standards to assist XPS users. One set of such guides has been published, and another is being assembled. Providing incremental bites of useful information is the goal of a series of papers on specific challenges to surface analysis with example solutions has been initiated as Notes and Insights papers in Surface and Interface Analysis. Examination of XPS-containing papers finds that information to establish the credibility and reproducibility of XPS results is often very incomplete. Unfortunately, ISO and ASTM standards require an amount of parameter reporting that seems excessive and unrealistic for many research publications. Initial approaches to develop and distribute a graded approach to parameter reporting are briefly described. Multiple efforts are underway to address the high rate of problems associated with photoelectron peak fitting. These include guides to peak fitting, guides to peak identification and fitting for specific elements, and the development of a peak fitting social network. The fitting social network is designed to facilitate interactions between new and experienced XPS users; analysts trying to fit XPS data (for publication or other reasons) can ask questions and establish dynamic conversations. Encouraging and enabling high-quality XPS analysis and reporting requires several different types of effort from all members of the surface and interface analysis community.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Introductory guide to backgrounds in XPS spectra and their impact on determining peak intensities

Photoelectron and Auger peaks are central to most of the important uses of x-ray photoelectron spectroscopy (XPS), and thus, they receive the most attention in many types of analysis. Quantitative chemical analysis using XPS requires the assessment of the intensities of the photoemission peaks of the elements detected. Determination of peak intensities requires separation of the photoelectron peak signals from the background on which the peaks rest. For the determination of peak area intensities, the background is subtracted from overall signal intensity. The spectral background is also critical when peak fitting is used to determine intensities of overlapping peaks, and the model of background used in this process can impact the results. In addition to the impact on quantitative analysis, information about the depth distribution of elements in the near surface region can often be obtained by visual inspection of the background and quantified using appropriate modeling. Here, this introductory guide provides some basic information about backgrounds in the XPS analysis, describes the types of background models that are commonly used, suggests some of their strengths and weaknesses, and provides examples of their use and misuse. Although the fundamental nature of some components of the background signals in XPS is not understood, indicating that none of the models in use are fully correct and the area is subject to active research, appropriate good practices have been established for most routine analysis. The guide describes good practices, identifies errors that frequently appear in the literature, and uses examples to demonstrate the impacts of background selections on determinations of peak intensities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

Fluid Physics in a Fluctuating Acceleration Environment

Our program of research aims at developing a stochastic description of the residual acceleration field onboard spacecraft (g-jitter) to describe in quantitative detail its effect on fluid motion. Our main premise is that such a statistical description is necessary in those cases in which the characteristic time scales of the process under investigation are long compared with the correlation time of g-jitter. Although a clear separation between time scales makes this approach feasible, there remain several difficulties of practical nature: (i), g-jitter time series are not statistically stationary but rather show definite dependences on factors such as active or rest crew periods; (ii), it is very difficult to extract reliably the low frequency range of the power spectrum of the acceleration field. This range controls the magnitude of diffusive processes; and (iii), models used to date are Gaussian, but there is evidence that large amplitude disturbances occur much more frequently than a Gaussian distribution would predict. The lack of stationarity does not constitute a severe limitation in practice, since the intensity of the stochastic components changes very slowly during space missions (perhaps over times of the order of hours). A separate analysis of large amplitude disturbances has not been undertaken yet, but it does not seem difficult a priori to devise models that may describe this range better than a Gaussian distribution. The effect of low frequency components, on the other hand, is more difficult to ascertain, partly due to the difficulty associated with measuring them, and partly because they may be indistinguishable from slowly changing averages. This latter effect is further complicated by the lack of statistical stationarity of the time series. Recent work has focused on the effect of stochastic modulation on the onset of oscillatory instabilities as an example of resonant interaction between the driving acceleration and normal modes of the system, and on cavity flow as an example of how an oscillatory response under periodic driving becomes diffusive if the forcing is random instead. This paper describes three different topics that illustrate behavior that is peculiar to a stochastic acceleration field. In the first case, we show that g-jitter can induce effective attractive or repulsive forces between a pair of spherical particles that are suspended in an incompressible fluid of different density provided that the momentum diffusion length is larger than the interparticle separation (as in the case in most colloidal suspensions). Second, a stochastic modulation of the control parameter in the vicinity of a pitchfork or supercritical bifurcation is known not to affect the location of the threshold. We show, however, that resonance between the modulation and linearly stable modes close to onset can lead to a shift in threshold. Finally, we discuss the classical problem of vorticity diffusion away from a plane boundary that is being vibrated along its own plane. Periodic motion with zero average vorticity production results in an exponential decay of the vorticity away from the boundary. Random vibration, on the other hand, results in power law decay away from the boundary even if vorticity production averages to zero.

Drolet, Francois↗