SEARCH · Engineering Papers

Results for “Precision Cleaning”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

116 records · Page 7

All sources NASA NTRS DOE OSTI

DOE OSTI2021

National Alliance for Water Innovation (NAWI) Resource Extraction Sector Technology Roadmap 2021

The National Alliance for Water Innovation (NAWI) is a research consortium formed to accelerate transformative research in desalination and treatment to lower the cost and energy required to produce clean water from nontraditional water sources and realize a circular water economy. NAWI’s goal is to enable the manufacturing of energy-efficient desalination technologies in the United States at a lower cost with the same (or higher) quality and reduced environmental impact for 90 percent of nontraditional water sources within the next 10 years. The nontraditional source waters of interest include brackish water; seawater; produced and extracted water; power, mining, industrial, municipal, and agricultural waste waters. When these desalination and treatment technologies are fully developed and utilized, they will be able to contribute to the water needs for many existing end-use sectors. NAWI has identified five end-use sectors that are critical to the U.S. economy for further exploration: Power, Resource Extraction, Industry, Municipal, and Agriculture (PRIMA). This Resource Extraction Sector roadmap aims to advance desalination and treatment of nontraditional source waters for beneficial use in public water supplies by identifying research and development (R&D) opportunities that help overcome existing treatment challenges. Under NAWI’s vision, the transition from a linear to a circular water economy with nontraditional source waters will be achieved by advancing desalination and reuse technologies in six key areas: Autonomous operations, Precision separations, Resilient treatment and transport, Intensified brine management, Modular membrane systems, and Electrified treatment systems, collectively known as the A-PRIME areas. Technological advances in these different areas will enable nontraditional source waters to achieve pipe parity with traditional supplies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Phenomenological model of the third-harmonic magnetic response due to superconducting fluctuations: Application to Sr 2 RuO 4

Here, we employ the phenomenological Lawrence-Doniach model to compute the contributions of the superconducting fluctuations to the third-harmonic magnetic response, denoted here by $\bar{M_3}$, which can be measured in a precise way using ac magnetic fields and lock-in techniques. We show that, in an intermediate temperature regime, this quantity behaves as the third-order nonlinear susceptibility, which shows a power-law dependence with the reduced temperature ε = $\frac{T-T_c}{T_c}$ as ε -5/2 . Very close to T c , however, $\bar{M_3}$ saturates due to the nonzero amplitude of the ac field. We compare our theoretical results with experimental data for three conventional superconductors—lead, niobium, and vanadium—and for the unconventional superconductor Sr 2 RuO 4 (SRO). We find good agreement between theory and experiment for the elemental superconductors, although the theoretical values for the critical field systematically deviate from the experimental ones. In the case of SRO, however, the phenomenological model completely fails to describe the data, as the third-harmonic response remains sizable over a much wider reduced temperature range compared to Pb, Nb, and V. We show that an inhomogeneous distribution of T c across the sample can partially account for this discrepancy, since regions with a locally higher T c contribute to the fluctuation $\bar{M_3}$ significantly more than regions with the “nominal” T c of the clean system. However, the exponential temperature dependence of $\bar{M_3}$ first reported by Pelc et al. [Nat. Commun. 10, 2729 (2019)] is not captured by the model with inhomogeneity. We conclude that, while inhomogeneity is an important ingredient to understand the superconducting fluctuations of SRO and other perovskite superconductors, additional effects may be at play, such as non-Gaussian fluctuations or rare-region effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Neutron Skin Measurement of 208Pb and 48Ca Using Parity Violating Electron Scattering

Parity-violating electron scattering experiments (PVES) provides a clean probe of neutron densities that is model independent and free from strong interaction uncertainties in interpretation. The PREX-2 and CREX experiments were run in 2019 and 2020 at Jefferson laboratory measured the nucleon skin thickness, the difference between the r.m.s. neutron radius Rn and the r.m.s. proton radius Rp, of 208Pb and 48Ca via parity violating electroweak asymmetry in the elastic scattering of longitudinally polarized electrons. PREX-2 experiment was performed with 950 MeV electrons scattered at a 5¿ angle with Q2 = 0.00616 ± 0.00004 (GeV/c)2, while CREX used 2182 MeV electrons at the same angle with Q2 = 0.0297 ± 0.0002 (GeV/c)2. For PREX-2 the measured asymmetry was AP V = 550 ± 16 (stat.) ± (syst.) ppb, which corresponds to Rskin = 0.278 ± 0.078 (exp.) ± 0.012 (theo.) fm. The CREX asymmetry was AP V = 2668 ± 106 (stat.) ± 40 (syst.) ppb, which corresponds to Rskin = 0.121 ± 0.026 (exp.) ±0.024 (model) fm. One of the crucial systematic uncertainty that PREX-2 and CREX were sensitive to was the non-parity violating asymmetries that resulted from the helicity correlated false asymmetries in the polarized electron beam. There was a lot of work put towards understanding and suppressing the asymmetries arising from these effects. The parity violating asymmetry measurement required a very precise determination of the electron beam polarization. To accurately determine the beam polarization, a Compton polarimeter was used during both PREX-2 and CREX. A careful alignment of the laser to the Fabry-Perot cavity, data analysis and systematic control was employed to get a precise beam polarization result for the experiments. The PREX-2 measurement has broad implications for increasing our knowledge about neutron star structure and the equation of state of nuclear matter. The combined PREX and CREX results will have implications for future energy density functional calculations and the theory of nuclear structure.

Premathilake, Sachinthani↗

DOE OSTI2022

Simulations of aerosol pH in China using WRF-Chem (v4.0): sensitivities of aerosol pH and its temporal variations during haze episodes

Aerosol pH is a fundamental property of aerosols in terms of atmospheric chemistry and its impact on air quality, climate, and health. Precise estimation of aerosol pH in chemical transport models (CTMs) is critical for aerosol modeling and thus influences policy development that partially relies on results from model simulations. We report the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) simulated PM 2.5 pH over China during a period with heavy haze episodes in Beijing, and explore the sensitivity of the modeled aerosol pH to factors including emissions of nonvolatile cations (NVCs) and NH 3 , aerosol phase state assumption, and heterogeneous production of sulfate. We find that default WRF-Chem could predict spatial patterns of PM 2.5 pH over China similar to other CTMs, but with generally lower pH values, largely due to the underestimation of alkaline species (NVCs and NH 3 ) and the difference in thermodynamic treatments between different models. Increasing NH 3 emissions in the model would improve the modeled pH in comparison with offline thermodynamic model calculations of pH constrained by observations. In addition, we find that the aerosol phase state assumption and heterogeneous sulfate production are important in aerosol pH predictions for regions with low relative humidity (RH) and high anthropogenic SO 2 emissions, respectively. These factors should be better constrained in model simulations of aerosol pH in the future. Analysis of the modeled temporal trend of PM 2.5 pH in Beijing over a haze episode reveals a clear decrease in pH from 5.2 ± 0.9 in a clean period to 3.6 ± 0.5 in a heavily polluted period. The increased acidity under more polluted conditions is largely due to the formation and accumulation of secondary species including sulfuric acid and nitric acid, even though being modified by alkaline species (NVCs, NH 3 ). Our result suggests that NO 2 oxidation is unlikely to be important for heterogeneous sulfate production during the Beijing haze as the effective pH for NO 2 oxidation of S(IV) is at a higher pH of ~6.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Cosmic recombination in the presence of primordial magnetic fields

Primordial magnetic fields (PMFs) may explain observations of magnetic fields on extragalactic scales. They are most cleanly constrained by measurements of cosmic microwave background radiation (CMB) anisotropies. Their effects on cosmic recombination may even be at the heart of the resolution of the Hubble tension. We present the most detailed analysis of the effects of PMFs on cosmic recombination to date. To this end we extend the public magneto-hydrodynamic code ENZO with a new cosmic recombination routine, Monte-Carlo simulations of Lyman-α photon transport, and a Compton drag term in the baryon momentum equation. The resulting code allows us, for the first time, to realistically predict the impact of PMFs on the cosmic ionization history and the clumping of baryons during cosmic recombination. Our results identify the importance of mixing of Lyman-α photons between overdense- and underdense- regions for small PMF strength. This mixing speeds up recombination beyond the speed-up due to clumping. We also investigate the effects of pecuilar flows on the recombination rate and find it to be small for small PMF strengths. For non-helical PMFs with a Batchelor spectrum we find a surprising dependency of results on ultra-violet magnetic modes. We further show that the increase in the ionization fraction at low redshift by hydrodynamic baryon heating due to PMF dissipation is completely compensated by the faster recombination from baryon clumping. In conclusion, the present study shall serve as a theoretical foundation for a future precise comparison of recombination with PMFs to CMB data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

$\rm {H\,\small {I}}$ constraints from the cross-correlation of eBOSS galaxies and Green Bank Telescope intensity maps

We present the joint analysis of Neutral Hydrogen ($\rm {H\,\small {I}}$) Intensity Mapping observations with three galaxy samples: the Luminous Red Galaxy (LRG) and Emission Line Galaxy (ELG) samples from the eBOSS survey, and the WiggleZ Dark Energy Survey sample. The $\rm {H\,\small {I}}$ intensity maps are Green Bank Telescope observations of the redshifted $21\rm cm$ emission on $100 \, {\rm deg}^2$ covering the redshift range 0.6 < z < 1.0. We process the data by separating and removing the foregrounds present in the radio frequencies with FastI ICA. We verify the quality of the foreground separation with mock realizations, and construct a transfer function to correct for the effects of foreground removal on the $\rm {H\,\small {I}}$ signal. We cross-correlate the cleaned $\rm {H\,\small {I}}$ data with the galaxy samples and study the overall amplitude as well as the scale dependence of the power spectrum. We also qualitatively compare our findings with the predictions by a semianalytical galaxy evolution simulation. The cross-correlations constrain the quantity $\Omega _{\rm {H\,\small {I}}} b_{\rm {H\,\small {I}}} r_{\rm {H\,\small {I}},{\rm opt}}$ at an effective scale k eff , where $\Omega _\rm {H\,\small {I}}$ is the $\rm {H\,\small {I}}$ density fraction, $b_\rm {H\,\small {I}}$ is the $\rm {H\,\small {I}}$ bias, and $r_{\rm {H\,\small {I}},{\rm opt}}$ the galaxy–hydrogen correlation coefficient, which is dependent on the $\rm {H\,\small {I}}$ content of the optical galaxy sample. At $k_{\rm eff}=0.31 \, h\,{\rm Mpc^{-1}}$ we find $\Omega _{\rm {H\,\small {I}}} b_{\rm {H\,\small {I}}} r_{\rm {H\,\small {I}},{\rm Wig}} = [0.58 \pm 0.09 \, {\rm (stat) \pm 0.05 \, {\rm (sys)}}] \times 10^{-3}$ for GBT-WiggleZ, $\Omega _{\rm {H\,\small {I}}} b_{\rm {H\,\small {I}}} r_{\rm {H\,\small {I}},{\rm ELG}} = [0.40 \pm 0.09 \, {\rm (stat) \pm 0.04 \, {\rm (sys)}}] \times 10^{-3}$ for GBT-ELG, and $\Omega _{\rm {H\,\small {I}}} b_{\rm {H\,\small {I}}} r_{\rm {H\,\small {I}},{\rm LRG}} = [0.35 \pm 0.08 \, {\rm (stat) \pm 0.03 \, {\rm (sys)}}] \times 10^{-3}$ for GBT-LRG, at z ≃ 0.8. We also report results at $k_{\rm eff}=0.24$ and $k_{\rm eff}=0.48 \, h\,{\rm Mpc^{-1}}$. With little information on $\rm {H\,\small {I}}$ parameters beyond our local Universe, these are amongst the most precise constraints on neutral hydrogen density fluctuations in an underexplored redshift range.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

COMBLE-ISLAS water isotopes in precipitation (COMBLEISLASISO)

During the measurement period, precipitation was sampled on daily to sub-daily basis with a sampling kit consiting of a clear plastic box (60x40x40 cm) mounted to a ground structure. Daily sampling lasted from 22 Feb to 24 Mar 2020. At a fixed time of day (10 UTC), samples were collected and the sampling box cleaned for the next sample. Additionally, during intense observations periods (IOPs) announced by ISLAS, ARMS scientists increased sampling frequency to sub-daily sampling. During the campaign period, 2 IOPs were conducted, with in total 12 samples taken. IOP1 lasted from 27 Feb 10 to 02 Mar 2020, and IOP2 lasted from 12 Mar to 14 Mar 2020. Solid precipitation in the box was then melted, transferred to an 8 ml glass vial, sealed and shipped to FARLAB (University of Bergen, Norway) for stable water isotope analysis. Measured stable isotope composition of precipitation samples will be related to conditions at other sampling locations, and at the evaporation site to inform about conservation of water isotope quantities. In the period from 22 Feb to 24 Mar, 23 daily samples were collected at 10 UTC for stable water isotope analysis. During the entire sampling period, a high variability of precipitation phase was encountered. Most samples were recovered in the form of graupel/snow (12 samples), as rain (7 samples), and the remaining samples fell as graupel, snow, rain or frozen rain. Precipitation amounts varied between <1 mm (26 Feb) and 140 mm (25 Feb) within the sampling box. Furthermore, higher-resolution sampling was conducted during 2 intense observation periods (IOPs). During IOP1, lasting from 27 Feb 10 UTC to 02 Mar 10 UTC, 7 samples were collected, all of them as solid phase precipitation. IOP2 lasted from 12 Mar 10 UTC to 14 Mar 09 UTC, and 5 samples (all as graupel/snow) were collected. Samples were processed according to FARLAB standard measurement procedures. In short, samples were transferred to 1.5 ml glass vials with rubber/PTFE septa (part #548-0907, VWR, USA). An autosampler (A0325, Picarro Inc) transferred ca. 2µl per injection into a high-precision vapourizer (A0211, Picarro Inc, USA) heated to 110°C. After blending with dry N2 (< 5 ppm H2O) the gas mixture was directed into the measurement cavity of a Cavity-Ring Down Spectrometer (L2140-i, Picarro Inc) for about 7 min with a typical water concentration of 20 000 ppm. Memory effects were reduced by two times measuring a vapour mixture at a mixing ratio of 50 000 ppm, obtained from 2 injections of 2 µl for 5 min at the beginning of each new sample vial. Thereafter, another 6 injections of 2 µl per sample were measured individually as described above, and averages of the last 5 injections were used for further processing. Three standards were measured at the beginning and end of each batch, including a drift standard DI2 (δD: -50.72±0.73 permil, δ18O: -7.63±0.10 permil), and for calibration the laboratory standards GLW (δD: -307.79±0.75 permil, δ18O: -40.02±0.07 permil) and EVAP2 (δD: 9.52±0.65 permil, δ18O: 1.81±0.13 permil). A detailed calibration report is included with the final uploaded data set.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Hydrogen Detection Strategies to Support H2@SCALE - The NREL Sensor Laboratory

Hydrogen represents a major pathway to decarbonize and stabilize the national and international energy industry and select manufacturing markets. To facilitate the development of hydrogen markets, the US Department of Energy initiated H2@Scale to bring together stakeholders to advance affordable hydrogen production, transport, storage, and utilization to increase revenue opportunities in multiple energy sectors. One major impediment to hydrogen implementation is cost. To expedite the use of hydrogen in energy and other markets, the United States announced in 2021 the Hydrogen Shot, which seeks to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). As the cost of hydrogen drops, new applications will emerge that will require unique configurations of existing equipment and infrastructure, and eventually lead to advances in the generation and utilization of hydrogen. As the hydrogen economy expands, sensors and detection methods will need to adapt to changing infrastructure demands to address the primary targets of health & safety, emissions monitoring, and process control. The NREL Sensor Laboratory is playing a pivotal role in advancing the use of hydrogen sensors and detection methodologies in each of these categories to support DOE's mission for safe and efficient utilization in emerging markets. Health & safety monitors are required to ensure that operators and facilities can react to unintended hydrogen releases, either as GH2, LH2, or as a constituent of blends (e.g., natural gas or ammonia). Current detection methodologies focus on safety applications to detect near its lower flammable limit (4 vol %), and typically include point sensors in applications such as fixed or mobile detectors (e.g., personal gas monitors). Methodologies amenable for area detection include acoustic, emerging optical imaging methods, and flame detectors. Comparable detection strategies can be utilized for emissions monitoring and quantization, however few methods can simultaneously cover both low (emissions) and high (health & safety) levels. Deployment of emission level detectors will be required to 1) reduce product loss through small but potentially significant leaks from an environmental or cost perspective, 2) reduce downtime of high demand systems by early identification of eminent system failures (leaks through pump or compressor seals indicative of impending failure), and 3) address potential emission monitoring requirements that may be set by regulating bodies. The first two points should be adopted by industry to reduce the cost-of-goods-sold. The third main category for hydrogen detection relates to process control and may be advantageous for many existing applications. Two main applications are emerging. For example, the purity requirements for hydrogen that is dispensed from refueling systems for hydrogen fuel cell electric vehicles (FCEV) is rigorously regulated by the Standard SAE J2719, which prescribes maximum allowable levels of multiple impurities in the hydrogen fuel and must be verified by a regulatory body. Hydrogen contaminant detectors (HCD) integrated to the fueling station can assure this compliance. HCDs must be able operate in 100% H2 backgrounds and be able to distinguish between multiple contaminants at low ppm to low ppb levels. Secondly, as a strategy to decarbonize the natural gas grid, there are proposals to blend hydrogen with natural gas. This blending will affect transport applications (pipeline infrastructure), stationary combustion systems (turbines), and consumer and commercial appliances. In the short-term, hydrogen levels up to 20% are proposed. Variations in the hydrogen level can have dramatic impact on the combustion process and on the potential response of safety sensors. These mixtures may be regulated so that the concentration at a delivery point must be monitored with high precision. However, routine maintenance may introduce background gases such as ambient air (with water) or maintenance gases (introduced with welding processes or adhesive outgassing.) Therefore, the detection methodology must be robust enough to recover or respond to various contaminants. Several reviews can be found in literature addressing sensing and detection technologies, including their limitations and applications. However, for most applications, limitations can be alleviated by combining various detection techniques either through system integration or implementation of machine learning methods (artificial intelligence). In this presentation, we will discuss several applications, highlight their current approach for hydrogen detection, and suggest detection strategies to supplement their limitations.

ENERGY STORAGE,HYDROGEN↗