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Results for “sequential experiment”

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At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Observation of Charmonium Sequential Suppression in Heavy-Ion Collisions at the Relativistic Heavy Ion Collider

We report measurements of charmonium sequential suppression in Ru+Ru and Zr+Zr collisions at $\sqrt{s_{NN}}$ =200 GeV with the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). The inclusive yield ratio of 𝜓⁡(2⁢S) to J/𝜓 as a function of transverse momentum is reported, along with the centrality dependence of the double ratio, defined as the 𝜓⁡(2⁢S) to J/𝜓 ratio in heavy-ion collisions relative to that in 𝑝 +𝑝 collisions. In the 0–80% centrality class, the double ratio is found to be 0.41±0.10 (stat)±0.03 (syst)±0.02 (ref), lower than unity with a significance of 5.6 standard deviations. This provides experimental evidence that 𝜓⁡(2⁢S) is significantly more suppressed than J/𝜓 in heavy-ion collisions at RHIC. This sequential suppression pattern seems to increase from peripheral to central collisions, but with no significant dependence on the transverse momentum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Data from a throughfall exclusion experiment: Fine root dynamics, morphology, chemistry, and AMF colonization across four lowland Panamanian forests

Fine roots regulate forest nutrient, carbon, and water cycling, yet their variation within and among tropical forests remains under-characterized. We quantified root productivity, disappearance, and stocks to 1 m using minirhizotron imaging, and we measured morphology, elemental composition [root carbon (C), root nitrogen (N), root phosphorus (P)], and arbuscular mycorrhizal fungi (AMF) colonization to 20 cm using ingrowth cores and sequential coring. Sampling took place in four distinct lowland Panamanian forests (32 plots; 8 per forest) from 2018 through 2022 under control and throughfall-exclusion (drought) treatments in the Panama Rainforest Changes with Experimental Drying (PARCHED) experiment.The dataset is presented as an Excel workbook with six tabs. The first tab is the data dictionary. Tab S1 contains ingrowth-core production and mortality, morphology and soil moisture. Tab S2 contains sequential-coring standing stocks with associated morphology and soil moisture. Tab S3 contains minirhizotron row data records to 1 m depth, including per-frame root length and diameter, normalized length metrics, and session timing. Tab S4 contains AMF colonization. Tab S5 contains fine-root chemistry at 0–10 cm, reporting %P, %C, %N, and C:N for samples collected via ingrowth cores and sequential-coring standing stocks. CSV mirrors for each tab are provided, and a KML file supplies coordinates for all 32 plots.Key variables span live and dead fine-root biomass (and coarse fractions where applicable), specific root length (SRL) and area (SRA), diameter, root tissue density (RTD), soil moisture, AMF colonization, root %N, %C, %P, and C:N, along with minirhizotron root length and diameter. Depth, season, treatment, and plot/site identifiers are included to support cross-tab integration and analysis from 0–100 cm (minirhizotron) and 0–20 cm (cores).Units are reported in-column and missing values are coded as NA. No special software is required to open or use the files (Excel, CSV, and KML compatible).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Inelastic Neutron Scattering Observation of Plasma-Promoted Nitrogen Reduction Intermediates on Ni/γ-Al 2 O 3

Plasma-assisted catalysis is an emerging technology for the atmospheric pressure and low bulk gas temperature synthesis of ammonia from molecular nitrogen and hydrogen. Direct evidence for plasma-induced surface reaction intermediates relevant to ammonia production, including surface hydrides and NH x (x = 1, 2, 3) species, has remained elusive. In this work, we report inelastic neutron scattering (INS) observations of alumina-supported Ni particles after treatment with N 2 and H 2 plasmas. INS experiments reveal the presence of NH x species and hydrides on Ni sites after exposure to sequential N 2 and H 2 plasma treatments. By separating exposure, we exclude the presence of plasma-phase reactions and demonstrate that these species are generated through plasma-facilitated surface reactions. Computed synthetic INS spectra of NH 3 , NH 2 and NH adsorbates on Ni support the experimental assignments of surface intermediates. The results directly implicate plasma stimulation of dinitrogen in generation of surface-bound nitrogen that participates in further hydrogenation reactions driven either thermally or with H 2 plasma.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Model for the Softening Factor within Stages of Work Hardening

A formulation for a dimensionless coefficient c b is derived that represents a scale of microstructural softening for alloys which follow Kocks-Mecking (K-M) work hardening behavior. The variation of the true plastic strain ε p between the proportional limit σ y and the strength σ u at the instability is determined using the Considère criterion. Parameterization of the model is limited to variables expressly measured within tensile experiments. Further development is now made for the softening factor c bi through the individual and sequential stages 3 and 4 of plastic deformation during K-M work hardening Q behavior. Application is shown for tensile test results of Ti-6Al-4V made by different additively manufactured (AM) processes. It is found that the variation in plastic strain as a function of c bi produces a continuous curve representative of the alloy system. The results of data analysis indicate that Θ o3 and c b3 increase, while Θ o4 and c b4 decrease, as the total plastic strain ε p increases. Furthermore, formulations derived for K-M stages 3 and 4 enable the evaluation of other material parameters such as the activation volume ν* for the onset of plastic deformation. This activation volume is found to be near constant, at a ν*-value of 0.353±0.036 nm 3 as computed using a strain-rate sensitivity of strength exponent m of 0.014, irrespective of the AM method used to produce the Ti-6Al-4V alloy.

36 MATERIALS SCIENCE↗

NASA NTRS1983

Health care delivery system for long duration manned space operations

Specific requirements for medical support of a long-duration manned facility in a low earth orbit derive from inflight medical experience, projected medical scenarios, mission related spacecraft and environmental hazards, health maintenance, and preventive medicine. A sequential buildup of medical capabilities tailored to increasing mission complexity is proposed. The space station health maintenance facility must provide preventive, diagnostic, and therapeutic medical support as immediate rescue capability may not exist.

Logan, J. S.↗

NASA NTRS1997

Autonomous Navigation with Ground-to-Space Doppler Measurements Referenced to a Temperature-Compensated Crystal Oscillator

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has spent several years developing operational Onboard Navigation Systems (ONS's) to provide real-time autonomous, high-accuracy navigation products for spacecraft using NASA's space and ground communication systems. The highly successful Tracking and Data Relay Satellite System (TDRSS) ONS (TONS) experiment on the Explorer Platform/Extreme Ultraviolet Explorer (EP/EUVE) spacecraft, launched June 7, 1992, flight-demonstrated the ONS for high-accuracy navigation using TDRSS forward- link communications services, In late 1994, the ground station ONS (GONS) experiment, using the same EP/EUVE flight hardware, flight-demonstrated the feasibility of high-accuracy autonomous navigation using ground station forward-link communication services, with an ultrastable oscillator (USO) as the frequency reference (1 part in 10(exp 10) over 24 hours). This paper provides a follow-on analysis of GONS performance to assess the navigation accuracy achievable if GONS uses the significantly less stable (5 parts in 10(exp 8) over 24 hours, compared with a specification of 1 part in 10(exp 6)) Temperature-Compensated Crystal Oscillator (TCXO), which is integral to the transponder, as a frequency reference rather than an external USO. The GONS TCXO experiment results from a 20-day period are used to project the expected performance of an operational system. The GONS processes Doppler data derived from nominally scheduled ground station forward-link communication services using a sequential estimation algorithm enhanced by a sophisticated process noise model to provide onboard orbit and frequency determination. To evaluate the navigation accuracies achievable if a TCXO were used, actual experiment data (which used the USO as the frequency reference) were corrupted with errors from real TDRSS one-way return tracking measurements taken from EP/EUVE's TCXO. Analysis of the GONS TCXO experiment performance indicates that real-time onboard position accuracies of better than 300 meters (1 sigma) are achievable with as few as two tracking contacts per day for the EP/EUVE 525-kilometer altitude, 28.5-degree inclination orbit, provided the TCXO is as stable as that in EP/EUVE's TDRSS transponder. GONS using a TCXO frequency reference provides a viable option for many upcoming spacecraft missions with moderate position accuracy requirements and an interest in reducing their operational costs with autonomous navigation.

Radomski, M. S.↗

NASA NTRS1981

Experiments on flow through one to four inlets of the orifice and Borda type

Choked flow rate and pressure profile data were taken on sequential axially aligned inlets of the orifice and Borda type. The configuration consisted of from two to four inlets spaced at two nominal separation distances of 0.7 and 30 diameters. At the nominal 30 diameter spacing, the reduced flow rate follows a simple empirical relation based on the reduced flow rate for a single inlet. At the nominal 0.7 diameter spacing, fluid jetting was prevalent at low temperatures and flow rates were the same as for a single inlet.

Hendricks, R. C.↗

NASA NTRS1982

Experiments on flow through one to four inlets of the orifice and Borda type

Hendricks, R. C.↗

DOE OSTI2024

Transfer learning for probabilistic localization of hidden cracks in concrete structures

Abstract The utility of discriminative supervised learning models built using multiple training-data sources is investigated for hidden crack localization in concrete. Feed-forward neural network (FFNN) is chosen as the model architecture, and transfer learning is used to assimilate the information obtained from different sources (computational physics simulations and laboratory experiments). The labeled training data consists of values of a damage index and the known locations of hidden cracks. The classification models need to learn how the presence of damage (hidden cracks) affects the damage index at different sensors for different test conditions. To this end, diagnostic FFNN models are built by sequentially adding and training new hidden layers to assimilate labeled information from computer models (different model geometries, test conditions, crack lengths, crack locations) and laboratory experiments on a plain cement slab. These transfer learning-based models are then used to localize damage in concrete specimens that reflect real-world conditions (i.e., specimens with steel reinforcement and randomly distributed aggregate). The actual damage state in these specimens is determined by extracting cores and performing petrographic studies on the extracted cores. The damage probability estimated by transfer learning-based models is compared with the petrographic damage rating index (DRI) to identify the most suitable approach to train the diagnostic models. The transfer learning-based diagnostic methodology shows promise and could be used in various structural health monitoring applications, where sufficient labeled data are typically not available from a single data source.

Miele, S.↗

NASA NTRS1996

Magnetospheric Atmospheric X-ray Imaging Experiment (MAXIE)

This report summarizes the activities sponsored by the Office of Naval Research for the Magnetospheric Atmospheric X-ray Imaging Experiment (MAXIE). The MAXIE instrument was developed as a joint activity of Lockheed, The Aerospace Corporation, and the University of Bergen, Norway. Lockheed was responsible for the overall management of the program, interfacing with the appropriate government agencies, the overall electrical and mechanical design, flight software, environmental testing, spacecraft integration activities, on orbit checkout, and data processing activities. The Magnetospheric Atmospheric X-ray Imaging Experiment (MAXIE), the ONR 401 experiment, is the first in a new class of satellite-borne remote sensing instruments. The primary innovation is the ability to obtain rapid, sequential, images with high sensitivity of the earth's X ray aurora from a low altitude polar orbiting satellite. These images can be used to identify dynamic temporal variations in the three-dimensional (energy and position) distribution of electron precipitation into the atmosphere. MAXIE was launched on the TIROS NOAA-13 satellite on 9 August 1993. The experiment performed well during its turn-on sequence; however, the spacecraft bus failed on 21 August 1993. New spacebased technologies successfully used in MAXIE were mixed-mode ASIC microcircuits, a zero torque scanning system with associated viscoelastic damping, a paraffin stow release mechanism, a parallel integrating PHA processor, a low noise Si(Li) sensor telescope, and an advanced thermal cooling system. MAXIE's on orbit operation, control of penetrating particle backgrounds, and scientific data indicated good overall performance.

Imhof, W. L.↗

NASA NTRS1993

Efficient partitioning and assignment on programs for multiprocessor execution

The general problem studied is that of segmenting or partitioning programs for distribution across a multiprocessor system. Efficient partitioning and the assignment of program elements are of great importance since the time consumed in this overhead activity may easily dominate the computation, effectively eliminating any gains made by the use of the parallelism. In this study, the partitioning of sequentially structured programs (written in FORTRAN) is evaluated. Heuristics, developed for similar applications are examined. Finally, a model for queueing networks with finite queues is developed which may be used to analyze multiprocessor system architectures with a shared memory approach to the problem of partitioning. The properties of sequentially written programs form obstacles to large scale (at the procedure or subroutine level) parallelization. Data dependencies of even the minutest nature, reflecting the sequential development of the program, severely limit parallelism. The design of heuristic algorithms is tied to the experience gained in the parallel splitting. Parallelism obtained through the physical separation of data has seen some success, especially at the data element level. Data parallelism on a grander scale requires models that accurately reflect the effects of blocking caused by finite queues. A model for the approximation of the performance of finite queueing networks is developed. This model makes use of the decomposition approach combined with the efficiency of product form solutions.

Standley, Hilda M.↗

NASA NTRS2013

SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws

With the introduction of new parallel architectures like the cell and multicore chips from IBM, Intel, AMD, and ARM, as well as the petascale processing available for highend computing, a larger number of programmers will need to write parallel codes. Adding the parallel control structure to the sequence, selection, and iterative control constructs increases the complexity of code development, which often results in increased development costs and decreased reliability. SequenceL is a high-level programming language that is, a programming language that is closer to a human s way of thinking than to a machine s. Historically, high-level languages have resulted in decreased development costs and increased reliability, at the expense of performance. In recent applications at JSC and in industry, SequenceL has demonstrated the usual advantages of high-level programming in terms of low cost and high reliability. SequenceL programs, however, have run at speeds typically comparable with, and in many cases faster than, their counterparts written in C and C++ when run on single-core processors. Moreover, SequenceL is able to generate parallel executables automatically for multicore hardware, gaining parallel speedups without any extra effort from the programmer beyond what is required to write the sequen tial/singlecore code. A SequenceL-to-C++ translator has been developed that automatically renders readable multithreaded C++ from a combination of a SequenceL program and sample data input. The SequenceL language is based on two fundamental computational laws, Consume-Simplify- Produce (CSP) and Normalize-Trans - pose (NT), which enable it to automate the creation of parallel algorithms from high-level code that has no annotations of parallelism whatsoever. In our anecdotal experience, SequenceL development has been in every case less costly than development of the same algorithm in sequential (that is, single-core, single process) C or C++, and an order of magnitude less costly than development of comparable parallel code. Moreover, SequenceL not only automatically parallelizes the code, but since it is based on CSP-NT, it is provably race free, thus eliminating the largest quality challenge the parallelized software developer faces.

Cooke, Daniel↗

DOE OSTI2023

Combined Data and Deep Learning Model Uncertainties: An Application to the Measurement of Solid Fuel Regression Rate

In complex physical process characterization, such as the measurement of the regression rate for solid hybrid rocket fuels, where both the observation data and the model used have uncertainties originating from multiple sources, combining these in a systematic way for quantities of interest (QoI) remains a challenge. In this paper, we present a forward propagation uncertainty quantification (UQ) process to produce a probabilistic distribution for the observed regression rate r. We characterized two input data uncertainty sources from the experiment (the distortion from the camera U c and the non-zero-angle fuel placement U Y ), the prediction and model form uncertainty from the deep neural network (U m ), as well as the variability from the manually segmented images used for training it (U s ). Here, we conducted seven case studies on combinations of these uncertainty sources with the model form uncertainty. The main contribution of this paper is the investigation and inclusion of the experimental image data uncertainties involved, and how to include them in a workflow when the QoI is the result of multiple sequential processes.

42 ENGINEERING↗

DOE OSTI2024

A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-scale Structure Using Sequential Methods

Strong gravitational lenses are a singular probe of the Universe’s small-scale structure—they are sensitive to the gravitational effects of low-mass (<10 10 M ⊙ ) halos even without a luminous counterpart. Recent strong-lensing analyses of dark matter structure rely on simulation-based inference (SBI). Modern SBI methods, which leverage neural networks as density estimators, have shown promise in extracting the halo-population signal. However, it is unclear whether the constraints from these models are limited by the methodology or the data. In this study, we introduce an accelerator-optimized simulation pipeline that can generate lens images with realistic subhalo populations in milliseconds. Leveraging this simulator, we identify the main limitation of our fiducial SBI analysis: training set size. We then adopt a sequential neural posterior estimation (SNPE) approach, allowing us to refine the training distribution to align with the observed data. Using only one-fifth as many mock Hubble Space Telescope images, SNPE matches the constraints on the low-mass halo population produced by our best nonsequential model. Our experiments suggest that an over 3 order-of-magnitude increase in training set size and GPU hours would be required to achieve an equivalent result without sequential methods. While the full potential of the existing lens sample remains to be explored, the notable improvement in constraining power enabled by our sequential approach highlights that current constraints are limited primarily by methodology and not the data itself. Moreover, our results emphasize the need to treat training set generation and model optimization as interconnected stages of any cosmological analysis using SBI.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1971

Experiment S051: Daytime sodium cloud

Daytime wind velocity measurements of the upper atmosphere as function of altitude were supposed to be gathered by Gemini 12 sequential photography of rocket made sodium clouds. Evaluation of the film was indicative that all 26 photographs were overexposed during the photographic sequences. The overexposures were caused by a camera shutter locked in the open position. Therefore, useful photographic data were not obtained for analysis.

Blamont, J. E.↗

NASA NTRS2012

A Practical Methodology for Quantifying Random and Systematic Components of Unexplained Variance in a Wind Tunnel

This paper documents a check standard wind tunnel test conducted in the Langley 0.3-Meter Transonic Cryogenic Tunnel (0.3M TCT) that was designed and analyzed using the Modern Design of Experiments (MDOE). The test designed to partition the unexplained variance of typical wind tunnel data samples into two constituent components, one attributable to ordinary random error, and one attributable to systematic error induced by covariate effects. Covariate effects in wind tunnel testing are discussed, with examples. The impact of systematic (non-random) unexplained variance on the statistical independence of sequential measurements is reviewed. The corresponding correlation among experimental errors is discussed, as is the impact of such correlation on experimental results generally. The specific experiment documented herein was organized as a formal test for the presence of unexplained variance in representative samples of wind tunnel data, in order to quantify the frequency with which such systematic error was detected, and its magnitude relative to ordinary random error. Levels of systematic and random error reported here are representative of those quantified in other facilities, as cited in the references.

Deloach, Richard↗

DOE OSTI2021

CO2 Capture Strategies via Mineralization with Industrial Waste Brines

Large coal-fired power plants (>500 MW) account for 30% of global CO2 emissions, and long-term management of this CO2 to is urgently needed mitigate global temperature increases. Sequestration of CO2 within stable mineral carbonates (e.g., CaCO3) represents an attractive emission reduction strategy because it offers a leakage-free alternative to geological storage of CO2 in an environmentally friendly form. We have previously described a mineralization process in which divalent cations are sourced from various waste streams (e.g., produced water and brackish water) and alkalinity is induced via regenerable ion-exchange materials (Bustillos et. al. Frontiers in Energy Research. 2020, 8, 352). In our process, aqueous carbonate-bearing streams with pH > 8 are produced by contacting fresh water and carbon dioxide with various ion-exchange materials (e.g., Na form zeolites or ion exchange resins). These streams are mixed with produced water containing varying concentrations (~0.01 – 1.0 M) of Ca2+ leading to the precipitation of solid calcium carbonate (PCC). This process has the advantages of using regenerable solids in a simple and continuous process to increase the pH of water by ion exchange instead of relying on the consumption of costly and unsustainable sources of alkalinity (e.g., sodium hydroxide). While once-through column experiments showed the above benefits, the same were yet to established in a steady-state process with recycle streams. In this work, we set up a process simulation to quantify the energy requirements and CO2 emissions associated with the process and seek optimal produced water compositions and CO2 concentrations (5 – 20 vol%). The process simulation was set up in ASPEN Plus using eRNTL as the thermodynamic property method and sequential modular strategy. Ion exchange alkaline solution was simulated using sodium hydroxide and validated against the experimental data obtained from once-through kinetic experiments. Nanofiltration and reverse osmosis membrane steps were also implemented for the separation of divalent cations and production of fresh water and a regeneration stream following mineralization. Sensitivity analysis was carried out using a range of produced water compositions (0.01 – 1.0 M Ca2+, 0.001 – 0.15 M Mg2+, 0.5 – 3.5 M Na+ and 0.0004 – 0.002 M Fe2+) according to the United States Geological Survey (USGS) database. Calcium carbonate yields increased with increasing CO2 concentrations and were maximized using produced water compositions with larger Ca2+ concentrations. Maximum calcium carbonate yields produced at 5 vol%, 12 vol% and 20 vol% CO2 were 2.3 mmol/L, 5.5 mmol/L, and 9.3 mmol/L, respectively, with the formation of brucite (a magnesium hydroxide phase, Mg(OH)2) and goethite (an iron hydroxide phase, FeOOH) as the primary contaminant phases (99% calcite, 0.6% brucite, 0.4% goethite), which agree with phases detected by XRD experimentally. These results indicate high purity calcium carbonate can be precipitated using industrial waste streams. Consequentially, energy consumption and net CO2 emissions were minimized where precipitated calcium carbonate was maximized for all produced water compositions and CO2 concentrations. Minimum energy consumptions were 0.21 kWh/ton CO2 processed, with 98% of the energy input required coming from the membrane filtration steps. Produced water compositions with large Na+ concentrations (> 0.5 M) were effective at reducing energy consumptions due to faster regeneration time of ion exchange materials. Additionally, calculated net CO2 emissions were negative for the process and ranged from -0.02 kg/ton CO2 to -0.15 kg/ton CO2 processed, indicating a low emission process. We will also present techno-economic assessment showing the economic benefits of the current process as an alternative to the addition of stoichiometric bases to induce alkalinity for the precipitation of CaCO3.

Simonetti, Dante↗

DOE OSTI2023

Combining Remotely Sensed Evapotranspiration and an Agroecosystem Model to Estimate Center‐Pivot Irrigation Water Use at High Spatio‐Temporal Resolution

Abstract Estimating irrigation water use accurately is critical for sustainable irrigation and studying terrestrial water cycle in irrigated croplands. However, irrigation is not monitored in most places, and current estimations of irrigation water use has coarse spatial and/or temporal resolutions. This study aims to estimate irrigation water use at the daily and field scale through the proposed model‐data fusion framework, which is achieved by particle filtering with two configurations (concurrent, CON, and sequential, SEQ) by assimilating satellite‐based evapotranspiration (ET) observations into an advanced agroecosystem model, ecosys . Two types of experiments using synthetic and real ET observations were conducted to study the efficacy of the proposed framework for estimating irrigation water use at the irrigated fields in eastern and western Nebraska, United States. The experiments using synthetic ET observations indicated that, for two major sources of uncertainties of ET difference between observations and model simulations, which are bias and noise, noise had larger impacts on degrading the estimation performance of irrigation water use than bias. For the experiments using real ET observations, monthly and annual estimations of irrigation water use matched well with farmer irrigation records, with Pearson correlation coefficient ( r ) around 0.80 and 0.50, respectively. Although detecting daily irrigation records was very challenging, our method still gave a good performance with RMSE, BIAS, and r around 2.90, 0.03, and 0.4 mm/d, respectively. Our proposed model‐data fusion framework for estimating irrigation water use at high spatio‐temporal resolution could contribute to regional water management, sustainable irrigation, and better tracking terrestrial water cycle.

Environmental Sciences & Ecology↗