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At least 415 records · Page 23

Methane Exhaust Measurements at Gathering Compressor Stations in the United States

Unburned methane entrained in exhaust from natural gas-fired compressor engines (“combustion slip”) can account for a substantial portion of station-level methane emissions. A novel in-stack, tracer gas method was coupled with Fourier transform infrared (FTIR) species measurements to quantify combustion slip from natural gas compressor engines at 67 gathering and boosting stations owned or managed by nine “study partner” operators in 11 U.S. states. The mean methane emission rate from 63 four-stroke, lean-burn (4SLB) compressor engines was 5.62 kg/h (95% CI = 5.15–6.17 kg/h) and ranged from 0.3 to 12.6 kg/h. The mean methane emission rate from 39 fourstroke, rich-burn (4SRB) compressor engines was 0.40 kg/h (95% CI = 0.37– 0.42 kg/h) and ranged from 0.01 to 4.5 kg/h. Study results for 4SLB engines were lower than both the U.S. EPA compilation of air pollutant emission factors (AP-42) and Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI) by 8 and 9%, respectively. Study results for 4SRB engines were 43% of the AP-42 emission factor and 8% of the GHGI emission factor, the latter of which does not distinguish between engine types. Total annual combustion slip from the U.S. natural gas gathering and boosting sector was modeled using measured emission rates and compressor unit counts from the U.S. EPA Greenhouse Gas Reporting Program. Modeled results [328 Gg/y (95% CI = 235–436 Gg/y) of unburned methane] would account for 24% (95% CI = 17–31%) of the 1391 Gg of methane emissions for “Gathering and Boosting Stations”, or 6% of the net emissions for “Natural Gas Systems” (5598 Gg) as reported in the 2020 U.S. EPA GHGI. In conclusion, gathering and boosting combustion slip emissions reported in the 2020 GHGI (374 Gg) fall within the uncertainty of this model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental Investigation of the Effect of Air-Handling and DME-Propane Blends on the Performance and Emissions of a 4-Cylinder CI Engine

Dimethyl ether (DME) is considered an excellent alternative to diesel because of its higher cetane number and lower carbon content. Additionally, DME can be blended with abundantly available propane with minimal modifications to the propane infrastructure. This paper focuses on an experimental investigation of the effect of air-handling i.e., boost pressure and exhaust gas recirculation (EGR), and DME-propane blends on the combustion and emissions performance of a light-duty, four-cylinder, compression ignition (CI) engine. Here, the boost pressure and EGR sweeps were carried out and showed that higher boost pressures resulted in increased brake thermal efficiencies (BTE) at the expense of higher NOx emissions which could be reduced by an increase in EGR. The fuel sweeps were carried out at 0, 15 and 25% propane (neat, 85% and 75% DME) with 0% and 25% EGR. The fuel sweeps indicated that the ignition delay (ID) increased and burn duration (BD) decreased monotonically when the blend increased to 25% propane/75% DME. The results suggest optimum engine performance with neat DME at 105 kPa boost pressure and 25% EGR with propane addition improving the BTE with negligible increase in emissions. Higher contents of Propane, up to 25%, did not affect the variability of combustion, with standard deviations of burn duration and peak cylinder pressures below 1% for all test cases.

air-handling↗

mRNA-LNP HIV-1 trimer boosters elicit precursors to broad neutralizing antibodies

Germline-targeting (GT) HIV vaccine strategies are predicated on deriving broadly neutralizing antibodies (bnAbs) through multiple boost immunogens. However, as the recruitment of memory B cells (MBCs) to germinal centers (GCs) is inefficient and may be derailed by serum antibody–induced epitope masking, driving further B cell receptor (BCR) modification in GC-experienced B cells after boosting poses a challenge. Using humanized immunoglobulin knockin mice, we found that GT protein trimer immunogen N332-GT5 could prime inferred-germline precursors to the V3-glycan–targeted bnAb BG18 and that B cells primed by N332-GT5 were effectively boosted by either of two novel protein immunogens designed to have minimum cross-reactivity with the off-target V1-binding responses. The delivery of the prime and boost immunogens as messenger RNA lipid nanoparticles (mRNA-LNPs) generated long-lasting GCs, somatic hypermutation, and affinity maturation and may be an effective tool in HIV vaccine development.

Science & Technology - Other Topics↗

Effects of stratification and charge cooling on combustion in a gasoline direct-injection compression ignition (GDCI) engine

With the development of low temperature engine combustion strategies, performance of gasoline-type fuels under compression ignition conditions has attracted extensive research interest. Meanwhile, for the sake of co-optimization of engines and fuels for future ground transportation, identification and evaluation of general fuel properties should be a core research priority instead of endless testing of specific fuels. In this study, the roles of fuel octane sensitivity in characterizing the ignition performance of gasoline surrogates have been systematically investigated under typical gasoline direct ignition compression ignition (GDCI) engine conditions using 3D combustion CFD simulation, especially considering the subsequent in-cylinder charge stratification and charge cooling. Two different operating conditions, high boost pressure low boost temperature (beyond-RON) case and low boost pressure high boost temperature (beyond-MON) case, were considered. By comparing with our previous zero-dimensional chemical kinetic study of gasoline surrogates in advanced compression ignition (ACI) engines, the effects of stratification and charge cooling on the combustion processes are investigated. It is found that different fuel octane sensitivities lead to slight difference in equivalence ratio stratification and charge cooling due to differences in volatility. However, fuel reactivity is still the more dominant factor than the stratification and charge cooling effects in determining combustion phasing. The present results help to justify the P-T domain framework for engine autoignition analysis of overlapping pressure-temperature trajectory with ignition delay iso-contour. Here, the results also provide useful guidance to the understanding of GCI combustion process, and to the evaluation of controlling fuel properties and the selection of alternative fuels in GCI engines.

33 ADVANCED PROPULSION SYSTEMS↗

Octane Index Applicability over the Pressure-Temperature Domain

Modern boosted spark-ignition (SI) engines and emerging advanced compression ignition (ACI) engines operate under conditions that deviate substantially from the conditions of conventional autoignition metrics, namely the research and motor octane numbers (RON and MON). The octane index (OI) is an emerging autoignition metric based on RON and MON which was developed to better describe fuel knock resistance over a broader range of engine conditions. Prior research at Oak Ridge National Laboratory (ORNL) identified that OI performs reasonably well under stoichiometric boosted conditions, but inconsistencies exist in the ability of OI to predict autoignition behavior under ACI strategies. Instead, the autoignition behavior under ACI operation was found to correlate more closely to fuel composition, suggesting fuel chemistry differences that are insensitive to the conditions of the RON and MON tests may become the dominant factor under these high efficiency operating conditions. This investigation builds on earlier work to study autoignition behavior over six pressure-temperature (PT) trajectories that correspond to a wide range of operating conditions, including boosted SI operation, partial fuel stratification (PFS), and spark-assisted compression ignition (SACI). A total of 12 different fuels were investigated, including the Co-Optima core fuels and five fuels that represent refinery-relevant blending streams. It was found that, for the ACI operating modes investigated here, the low temperature reactions dominate reactivity, similar to boosted SI operating conditions because their PT trajectories lay close to the RON trajectory. Additionally, the OI metric was found to adequately predict autoignition resistance over the PT domain, for the ACI conditions investigated here, and for fuels from different chemical families. This finding is in contrast with the prior study using a different type of ACI operation with different thermodynamic conditions, specifically a significantly higher temperature at the start of compression, illustrating that fuel response depends highly on the ACI strategy being used.

02 PETROLEUM↗

Automatic Search of Cataclysmic Variables Based on LightGBM in LAMOST-DR7

The search for special and rare celestial objects has always played an important role in astronomy. Cataclysmic Variables (CVs) are special and rare binary systems with accretion disks. Most CVs are in the quiescent period, and their spectra have the emission lines of Balmer series, HeI, and HeII. A few CVs in the outburst period have the absorption lines of Balmer series. Owing to the scarcity of numbers, expanding the spectral data of CVs is of positive significance for studying the formation of accretion disks and the evolution of binary star system models. At present, the research for astronomical spectra has entered the era of Big Data. The Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) has produced more than tens of millions of spectral data. the latest released LAMOST-DR7 includes 10.6 million low-resolution spectral data in 4926 sky regions, providing ideal data support for searching CV candidates. To process and analyze the massive amounts of spectral data, this study employed the Light Gradient Boosting Machine (LightGBM) algorithm, which is based on the ensemble tree model to automatically conduct the search in LAMOST-DR7. Finally, 225 CV candidates were found and four new CV candidates were verified by SIMBAD and published catalogs. This study also built the Gradient Boosting Decision Tree (GBDT), Adaptive Boosting (AdaBoost), and eXtreme Gradient Boosting (XGBoost) models and used Accuracy, Precision, Recall, the F1-score, and the ROC curve to compare the four models comprehensively. Experimental results showed that LightGBM is more efficient. The search for CVs based on LightGBM not only enriches the existing CV spectral library, but also provides a reference for the data mining of other rare celestial objects in massive spectral data.

79 ASTRONOMY AND ASTROPHYSICS↗

Computationally Selected Multivalent HIV-1 Subtype C Vaccine Protects Against Heterologous SHIV Challenge

Background: The RV144 trial in Thailand is the only HIV-1 vaccine efficacy trial to date to demonstrate any efficacy. Genetic signatures suggested that antibodies targeting the variable loop 2 (V2) of the HIV-1 envelope played an important protective role. The ALVAC prime and protein boost follow-up trial in southern Africa (HVTN702) failed to show any efficacy. One hypothesis for this is the greater diversity of subtype C viruses in southern Africa relative to CRF01_AE in Thailand. Methods: Here, we determined whether an ALVAC prime with computationally selected gp120 boost immunogens maximizing coverage of diversity of subtype C viruses in the variable V1 and V2 regions (V1V2) improved the protection of non-human primates (NHPs) from a heterologous subtype C SHIV challenge compared to more traditional regimens. Results: An ALVAC prime with Trivalent subtype C gp120 boosts resulted in statistically significant protection from repeated intrarectal SHIV challenges compared to the control. Evaluation of the immunogenicity of each vaccine regimen at the time of challenge demonstrated that different gp120 combination boosts elicited similar high magnitudes of gp120 and breadth of V1V2-binding antibodies, as well as strong Fc-mediated immune responses. Low-to-no neutralization of the challenge virus was detected. A Cox proportional hazard analysis of five pre-selected immune parameters at the time of challenge identified ADCC against the challenge envelope as a correlate of protection. Systems serology analysis revealed that immune responses elicited by the different vaccine regimens were distinct and identified further correlates of resistance to infection. Conclusions: Computationally designed vaccines with maximized subtype C V1V2 coverage mediated protection of NHPs from a heterologous Tier-2 subtype C SHIV challenge.

Immunology↗

DME-to-Propane Mixture Effects on a Light Duty Compression Ignition Engine

Fuels that can be produced in a sustainable manner are of high interest because they can provide an essential step toward net zero emissions vehicles. This study examines the combustion of two such fuels, Dimethyl Ether (DME) and propane, in a compression ignition, 4-cylinder, 2.2L engine running with mixtures of DME-to-Propane ranging of 100%-0%, 85%-15%, 75%-25%, and 65%-35% by weight. Testing was conducted at 2000rpm - 100Nm, an important representative point in the FTP certification cycle. For each fuel mixture, conditions tested include sweeps of boost, EGR and injection pressure. Here, tests are mainly conducted at a constant combustion timing with CA10 of -1 deg with respect to TDC, with an engine controller combustion feedback system based on in-cylinder sampling of pressure. Trends of NOx, HC, and CO are similar for the range of DME-to-propane, from 100%-0% to 75%-25%. Boost and injection pressures had the most notable impact on the heat release traces. Higher boost, from stoichiometric to lean resulted in approximately a 3-5% increase on cycle efficiency. Fuel injection pressures resulted in about 1% gain per 200bar. Results also illustrated that EGR is effective in reducing NOx but causes notable degradation of cycle efficiency. The emissions for DME-propane mixtures with 65%-35% had a different trend, with CO and HC exceeding the runs with lower propane content by 2 to 3-fold. As propane content increases, the pressure rise rates become higher, and with 65%-35% mixtures, rates easily exceed 12bar/deg. The increased rise rates correlate with early injection timings but the rates can be reduced, with higher boost and lower injection pressures. The result of the approach, however, leads to lower thermal efficiencies, decreasing efficiency by over 5% between neat DME and the highest propane ratios.

Combustion and combustion processes↗

Comprehensive Efficiency Analysis of Current Source Inverter Based on CSI-Type Double Pulse Test and Genetic Algorithm

A current-source inverter (CSI) has a natural output voltage boost feature that can be advantageous for traction applications. Switching frequency is one of the easily-controlled variables that can be adjusted to improve the CSI efficiency at different operating points when the boost function is used. This paper investigates a CSI-based double-pulse test (DPT) measurement that mimics normal operation of the CSI. A loss model of the CSI is developed based on the CSI-type DPT experimental results. The impacts of the switching frequency and voltage boost ratio on the CSI efficiency and output voltage ripple are investigated. Based on the loss model, a genetic algorithm has been introduced that makes it possible to optimize the CSI's switching frequency and modulation index to maximize its efficiency under any desired operating condition.

current-source inverter, genetic algorithm, SPM ma↗

Operation and Control of Electric Vehicle Charger with Enhanced Dynamic Performance Under Non-Ideal Grid Voltage Condition

This paper presents a three-phase electric vehicle charger connected to the grid, featuring multiple boost converters on the DC side, specifically designed to ensure smooth, oscillation-free power transfer during unsymmetrical voltage sags. Precise control mechanisms are implemented on the boost converter side to regulate both voltage and current on the electric vehicle side, thereby maintaining optimal charging conditions. The control architecture for both the grid-connected and boost converter components is based on the Lyapunov energy function, which is employed to achieve superior dynamic performance and stability. The system's robustness and reliability are demonstrated through its ability to maintain stable operation and efficient power transfer despite fluctuations in grid conditions. Furthermore, the implementation of Lyapunov-based control ensures rapid response and minimal energy loss, enhancing the overall efficiency of the system. To validate the effectiveness of this approach, a comprehensive model of the system was developed and tested using MATLAB/Simulink, with detailed computer simulations conducted across various significant case studies.

DC-DC boost converter↗

Current Source Inverter Based Large Constant Power Speed Ratio SPM Machine Drive for Traction Applications

A high-performance surface permanent magnet (SPM) machine drive with an extended constant power speed ratio is proposed using a current source inverter (CSI) for a traction application. The constant-power operation regions of an SPM machine can be extended in an appealing fashion by taking advantage of the output voltage boost capability of the CSI. The CSI is naturally a boost-type converter, in contrast to the voltage source inverter (VSI) which has buck-type characteristics. To investigate the value of the CSI voltage boost feature, a new traction motor with higher rated voltage and lower rated current has been designed and compared to the motor that would be used with a VSI. The lower CSI current makes it possible to reduce the mass of the inverter and output power cable, benefiting power density and cost reduction. The SPM machine is modeled in the synchronous reference frame including the effect of the ac filter capacitors at the CSI output terminals. The capability of extending the speed range of the proposed motor is verified via closed-form analysis and FEA simulation, and its performance characteristics are compared with those of a VSI-based SPM motor of the same type.

42 ENGINEERING↗

Celestial amplitudes from UV to IR

Celestial amplitudes represent 4D scattering of particles in boost, rather than the usual energy-momentum, eigenstates and hence are sensitive to both UV and IR physics. We show that known UV and IR properties of quantum gravity translate into powerful constraints on the analytic structure of celestial amplitudes. For example the soft UV behavior of quantum gravity is shown to imply that the exact four-particle scattering amplitude is meromorphic in the complex boost weight plane with poles confined to even integers on the negative real axis. Would-be poles on the positive real axis from UV asymptotics are shown to be erased by a flat space analog of the AdS resolution of the bulk point singularity. The residues of the poles on the negative axis are identified with operator coefficients in the IR effective action. Far along the real positive axis, the scattering is argued to grow exponentially according to the black hole area law. Exclusive amplitudes are shown to simply factorize into conformally hard and conformally soft factors. The soft factor contains all IR divergences and is given by a celestial current algebra correlator of Goldstone bosons from spontaneously broken asymptotic symmetries. The hard factor describes the scattering of hard particles together with the boost-eigenstate clouds of soft photons or gravitons required by asymptotic symmetries. These provide an IR safe S-matrix for the scattering of hard particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dark matter raining on DUNE and other large volume detectors

Direct detection is a powerful means of searching for particle physics evidence of dark matter (DM) heavier than about a GeV with o(kiloton) volume, low-threshold detectors. In many scenarios, some fraction of the DM may be boosted to large velocities enhancing and generally modifying possible detection signatures. We investigate the scenario where 100% of the DM is boosted at the Earth due to new attractive long-range forces. This leads to two main improvements in detection capabilities: (1) the large boost allows for detectable signatures of DM well below a GeV at large-volume neutrino detectors, such as DUNE, Super-K, Hyper-K, and JUNO, as possible DM detectors, and (2) the flux at the Earth’s surface is enhanced by a focusing effect. In addition, the model leads to a significant anisotropy in the signal with the DM flowing dominantly vertically at the Earth’s surface instead of the typical approximately isotropic DM signal. We develop the theory behind this model and also calculate realistic constraints using a detailed GENIE simulation of the signal inside detectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Delegated Regressor, A Robust Approach for Automated Anomaly Detection in the Soil Radon Time Series Data

We propose a new method based on the idea of delegating regressors for predicting the soil radon gas concentration (SRGC) and anomalies in radon or any other time series data. The proposed method is compared to different traditional boosting e.g., Extreme Gradient Boosting (EGB) and simple regression methods e.g., support vector regressors with linear kernel and radial kernel in terms of accurate predictions. R language has been used for the statistical analysis of radon time series (RTS) data. The results obtained show that the proposed methodology predicts SRGC more accurately when compared to different traditional boosting and regression methods. The best correlation is found between the actual and predicted radon concentration for window size of 2 i.e., two days before and after the start of seismic activities. RTS data was collected from 05 February 2017 to 16 February 2018, including 7 seismic events recorded during the study period. Findings of study show that the proposed methodology predicts the SRGC with more precision, for all the window sizes, by overlapping predicted with the actual radon time series concentrations.

54 ENVIRONMENTAL SCIENCES↗

Self-calibrating optical galaxy cluster selection bias using cluster, galaxy, and shear cross-correlations

ABSTRACT The clustering signals of galaxy clusters are powerful tools for self-calibrating the mass–observable relation and are complementary to cluster abundance and lensing. In this work, we explore the possibility of combining three correlation functions – cluster lensing, the cluster–galaxy cross-correlation function, and the galaxy autocorrelation function – to self-calibrate optical cluster selection bias, the boosted clustering and lensing signals in a richness-selected sample mainly caused by projection effects. We develop mock catalogues of redMaGiC-like galaxies and redMaPPer-like clusters by applying halo occupation distribution models to N-body simulations and using counts-in-cylinders around massive haloes as a richness proxy. In addition to the previously known small-scale boost in projected correlation functions, we find that the projection effects also significantly boost three-dimensional correlation functions to scales of 100 $h^{-1} \, \rm Mpc$. We perform a likelihood analysis assuming survey conditions similar to the Dark Energy Survey and show that the selection bias can be self-consistently constrained at the 10 per cent level. We discuss strategies for applying this approach to real data. We expect that expanding the analysis to smaller scales and using deeper lensing data would further improve the constraints on cluster selection bias.

Astronomy & Astrophysics↗

Relativistic corrections to the correlated basis function effective nuclear Hamiltonian

We discuss the inclusion of relativistic boost corrections into the correlated basis function effective nuclear Hamiltonian, derived from a realistic model of two- and three-nucleon interactions using the formalism of correlated basis functions and the cluster expansion technique. Different procedures to take into account the effects of boost interactions are compared on the basis of the ability to reproduce the nuclear matter equation of state obtained from accurate quantum many-body calculations. Furthermore, the results of our study show that the repulsive contribution of the boost interaction significantly depends on the underlying model of the nonrelativistic potential. On the other hand, the dominant relativistic correction turns out to be the corresponding reduction of the strength of repulsive three-nucleon interactions, leading to a significant softening of the equation of state of nuclear matter at supranuclear densities.

Neutron stars & pulsars↗

Anomaly detection search for new resonances decaying into a Higgs boson and a generic new particle $X$ in hadronic final states using $\sqrt{s}$ = 13 TeV $pp$ collisions with the ATLAS detector

A search is presented for a heavy resonance $Y$ decaying into a Standard Model Higgs boson $H$ and a new particle $X$ in a fully hadronic final state. The full Large Hadron Collider run 2 dataset of proton-proton collisions at $\sqrt{s}$ = 13 TeV collected by the ATLAS detector from 2015 to 2018 is used and corresponds to an integrated luminosity of 139 fb –1 . The search targets the high $Y$-mass region, where the $H$ and $X$ have a significant Lorentz boost in the laboratory frame. A novel application of anomaly detection is used to define a general signal region, where events are selected solely because of their incompatibility with a learned background-only model. It is constructed using a jet-level tagger for signal-model-independent selection of the boosted $X$ particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark $X$ decay into two quarks, covering topologies where the $X$ is reconstructed as either a single large-radius jet or two smallradius jets. The analysis selects Higgs boson decays into $b$$\overline{b}$, and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section $σ$ ($pp$ → $Y$ → $XH$ → $q$$\overline{q}$$b$$\overline{b}$) for signals with $m_Y$ between 1.5 and 6 TeV and $m_X$ between 65 and 3000 GeV

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗