Topic Refresher: The Power Triangle
This fact sheet provides an overview on active, reactive, and apparent power.
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This fact sheet provides an overview on active, reactive, and apparent power.
We outline the concrete steps involved in building prescriptive master integrand bases for scattering amplitudes beyond the planar limit. We highlight the role of contour choices in such bases, and illustrate the full process by constructing a complete, triangle power-counting basis at two loops for six particles. We show how collinear contour choices can be used to divide integrand bases into separately finite and divergent subspaces, and how double-poles can be used to further subdivide these spaces according to (transcendental) weight. Complete details of the basis constructed for six particles is provided in the supplementary material.
Ion mobility separations are usually performed in linear channels, which, when extended, can have a large footprint. In this work, we explored the performance of an ion mobility device with a curved architecture which can have a more compact form. The Co-centric Ion Mobility Spectrometer (CIMS) works by manipulating ions between two co-centric surfaces, each containing a serpentine track. The mobility separation inside CIMS is achieved using traveling waveforms (TWs). We initially evaluated the device using ion trajectory simulations using SIMION, which indicated that when ions traveled circularly inside CIMS, they resulted in similar resolving powers and transmitted m/z range as traveling in a straight path in structures for lossless ion manipulations (SLIM). We then performed experimental validation of CIMS in conjunction with a TOF MS. The CIMS was made of 2 flexible printed circuit board materials folded into concentric cylinders separated by a gap of 2.8 mm. The device was about 50 mm diameter × 152 mm long and provided 1.846 m of serpentine path length. Three sets of mixtures (Agilent tune mixture, tetraalkylammonium salts, and 8 peptide mixture) and four traveling waveform profiles (square, sine, triangle, and sawtooth) were used. The sawtooth TW profile produced a slightly higher resolving power for the Agilent tuning mixture and tetraalkylammonium ions. The average resolving power for Agilent tune mixture ions ranged from 37 (using sawtooth TW) to 27 (using square TW). For tetraalkylammonium ions, the average resolving powers ranged from 45 (sawtooth TW) to 31 (square TW). For the peptide mixture ions, the resolving power was similar among the four TW profiles and ranged from 51 to 56. The average percent error in TW CCS for the peptide mixture ions ranged was about 0.4%. In conclusion, the new device showed promising results for a device made of a flexible printed circuit board material, but improvements are needed to further increase the resolving power.
Structures for lossless ion manipulations (SLIM) have recently enabled a powerful implementation of traveling wave ion mobility spectrometry (TWIMS) for ultra-high resolution separations. However, optimization of experimental parameters remains challenging. Most TWIMS separations have utilized square-shaped waveforms applied by time-dependent voltage stepping across a repeating sets of electrodes; however, alternative waveforms may provide further improvements to resolution. In this work, we characterize five waveforms (including square and sine) in terms of their transmission efficiency, IMS resolution, and resolving power, and explore the effects of TW amplitude and speed on the performance of each. We found, consistent with previous work, separations were generally improved with higher TW amplitudes, moderately improved by lower speeds (limited by ion ‘surfing’ with the waves), and found decreases in signal intensity at the extremes of operating conditions. The triangle and asymmetric ‘ramp forward’ shaped profiles were found to provide modestly greater resolution and resolving power, an observation we tentatively attribute to their relatively uniform fields and minimal low-field regions.
Experiments are described, and results are provided, for the duplication of the first-ever triton-deuterium (colloquially referred to as DT) fusion experiment accidentally performed by A.J. Ruhlig in 1938, but forgotten in the published scientific literature. Here, we find that Ruhlig overestimated the ratio of the triton-deuterium over deuteron-deuterium neutron yields in his secondary reaction (Reaction-in-Flight) experiment compared to modern theoretical calculations and our duplication of his experiment using modern neutron detection methods. Nevertheless, Ruhlig’s observation provided the motivation for the application of DT fusion after World War II and its more recent importance in peaceful energy production at DT fusion facilities around the world. Additionally, the experimental technique used in the present work provides a novel approach for checking on low-energy triton stopping powers in deuterium containing compounds.
Triangles are the simplest non-trivial subgraphs and triangle counting is used in a number of different applications. The order in which vertices are processed in triangle counting strongly effects the amount of work that needs to be done (and thus the overall performance). Ordering vertices by degree has been shown to be one particularly effective ordering approach. However, for graphs with skewed degree distributions (such as power-law graphs), ordering by degree effects the distribution of work; parallelization must account for this distribution in order to balance work among workers. In this paper we provide an in- depth analysis of the ramifications of degree-based ordering on parallel triangle counting. We present approach for partitioning work in triangle counting, based on cyclic distribution and some surprisingly simple C++ implementations. Experimental results demonstrate the effectiveness of our approach, particularly for power-law (and social network) graphs.
EPRI, Pacific Northwest National Laboratory, RTI International, and their project collaborators developed an engineering-scale test of a new water-lean solvent, N-(2-ethoxyethyl)-3-morpholinopropan-1-amine (EEMPA or 2-EEMPA) as a post-combustion CO 2 capture solvent for power plant applications. This test was conducted using the Pilot Solvent Test Unit at the National Carbon Capture Center. The primary objective of this test was to collect long-term data operating EEMPA with both coal- and natural gas-representative flue gases at the approximately 0.5 MW e -equivalent scale (5–10 metric tons CO 2 /day captured). This report details the activities preparing for that test, data collected during the test campaign, and analyses and interpretations of that data.
The Energy Modeling Forum 37 study is organized around carbon dioxide (CO 2 ) mitigation scenarios reaching net-zero CO 2 emissions by 2050 in the United States. Here, this paper summarizes the potential contribution of bioenergy use in the electric power, transportation, industrial, and buildings sectors toward meeting that target based on model results. Thirteen modeling teams reported bioenergy consumption in the Reference and Net Zero scenarios. Consumption of bioenergy increased over time in the Reference scenario, from an average across models of 3.2 exajoules (EJ) in 2020 to 3.8 EJ in 2050. Average bioenergy consumption in 2050 increased further to 7.3 EJ in the Net Zero scenario. All scenarios that reach net-zero emissions required some form of carbon dioxide removal to offset emissions that are difficult to reduce. Carbon dioxide removal using bioenergy with CO 2 capture and storage (BECCS) varies widely across models, up to 1000 Mt CO 2 in 2050. Some models rely instead on direct air carbon capture and storage (DACCS), up to 2200 Mt CO 2 , and others use a combination of BECCS and DACCS. Model results show a strong inverse relationship between the amounts of BECCS and DACCS deployed. All modeling teams assumed a carbon sink from land use, land use change, and forestry, further offsetting a portion of emissions from fossil fuels and industry that are expensive to eliminate. Bioenergy consumption in 2050 decreased by an average of 1.5 EJ across eight models in a Net Zero+ scenario relative to the Net Zero scenario, due in part to a lower equilibrium carbon price resulting from optimistic cost assumptions for all energy technologies.
This final technical report submitted to DOE/NETL presents all the research activities performed during the Cooperative Agreement DE-FE0032218 entitled Second Generation Non-Aqueous Solvents (GEN2NAS) for CO 2 Capture from Natural Gas Combined Cycle Plants, which spanned from April 2023 through March 2025. In this project, Research Triangle Institute (RTI) International has developed the second-generation of its non-aqueous solvent (NAS), herein referred to as GEN2NAS, to remove carbon dioxide (CO 2 ) from natural-gas combined cycle (NGCC) flue gas. The technology aims to substantially reduce the cost of CO 2 capture while minimizing the environmental impacts through lower secondary emissions and wastewater generated from the CO 2 capture plant.
We explore the effective field theory of a vector field $X^μ$ that has a Stückelberg mass. The absence of a gauge symmetry for $X^μ$ implies Lorentz-invariant operators are constructed directly from Xμ. Beyond the kinetic and mass terms, allowed interactions at the renormalizable level include $X_μX^μH^†H, (X_μX^μ)^2$, and $X_μj^μ$, where $j^μ$ is a global current of the SM or of a hidden sector. We show that all of these interactions lead to scattering amplitudes that grow with powers of $\sqrt{s}/m_X$, except for the case of $X_μj^μ$ where $j^μ$ is a nonanomalous global current. The latter is well-known when $\textit{X}$ is identified as a dark photon coupled to the electromagnetic current, often written equivalently as kinetic mixing between $\textit{X}$ and the photon. The power counting for the energy growth of the scattering amplitudes is facilitated by isolating the longitudinal enhancement. We examine in detail the interaction with an anomalous global vector current $X_μj^μ_{\text{anom}}$, carefully isolating the finite contribution to the fermion triangle diagram. We calculate the longitudinally-enhanced observables $Z → X_γ$ (when $m_X < m_Z), f\bar{f} → X_γ$, and $Z_γ → Z_γ$ when $\textit{X}$ couples to the baryon number current. Introducing a "fake" gauge-invariance by writing $X^μ = A^μ – ∂^μπ/m_X$, the would-be gauge anomaly associated with $A_μj^μ_{\text{anom}}$ is canceled by $j^μ_{\text{anom}}∂_μπ/m_X$; this is the four-dimensional Green-Schwarz anomaly-cancellation mechanism at work. Our analysis demonstrates there is a much larger set of possible interactions that an EFT with a Stückelberg vector field can have, revealing scattering amplitudes that grow with energy. The growth of these amplitudes can be tamed by a dark Higgs sector, but this requires dark Higgs boson interactions (and reintroduces fine-tuning in the dark Higgs sector) that can be separated from X interactions only in the limit $g \ll 1$ .
A joint experimental and numerical study is performed to observe the characteristics of a supercritical carbon dioxide turbulent mixing layer in the presence of strong nonlinearities in the thermodynamic and transport properties. A bespoke experimental setup is designed and employed for this purpose and provides insight into macroscopic mixing behavior. The mixing is experimentally observed using two techniques: shadowgraphy and spontaneous Raman scattering. Qualitative and quantitative intensity fields obtained via these techniques yield instantaneous and mean density data. Spanwise temperature data is also collected using analogue resistance temperature detectors. These measurements are used to quantify the level of mixed material within the field. The experimental data are supplemented by a companion high-fidelity numerical study. The numerical results are obtained through fully resolved, three-dimensional direct numerical simulation. The numerical dataset permits observation of the near-field mixing characteristics, which are difficult to measure experimentally due to the rapid dynamics and sharp thermophysical gradients in this area. Qualitative field visualizations are presented, followed by quantitative mixed material results and observations regarding thermodynamic property trends at select locations within the field. One-dimensional spectra of the turbulent kinetic energy and solenoidal dissipation are provided to observe the spectral characteristics of the flow. Reynolds stress anisotropy is analyzed graphically through anisotropy invariance maps (Lumley triangles). The mixing quantification, spectral data and anisotropy analysis of a flow at these thermodynamic conditions represent the main outcomes of the work.
Quantum annealing is a powerful tool for solving and approximating combinatorial optimization problems, such as graph partitioning, community detection, centrality, routing problems, and more. In this paper we explore the use of quantum annealing as a tool for use in exploring combinatorial mathematics research problems. We consider the monochromatic triangle problem and the Ramsey number problem, both examples of graph coloring. Conversion to quadratic unconstrained binary optimization (QUBO) form is required to run on quantum hardware. While the monochromatic triangle problem is quadratic by nature, the Ramsey number problem requires the use of order reduction methods for a quadratic formulation. The goal is to provide a method for producing special colorings of graphs which if successful would provide lower bounds for certain Ramsey numbers. We discuss implementations, limitations, and results when running on the D-Wave Advantage quantum annealer.
This article describes the design, assembly, and implementation of a hand-held, magnetic-field-based sensor system that can be adapted for a variety of sensing applications. The miniaturized system is based on Chemical Identification by Magneto-Elastic Sensing (ChIMES) technology, which uses three concentric solenoid coils to wirelessly interrogate a sensor body comprised of a response material coupled to a magnetoelastic wire. The response material expands when it encounters a target, imposing mechanical stress on the wire and altering its magnetic permeability. The sensor bodies are passive, requiring no external power source, and they are small, measuring about 15 mm in length and 3.0 mm in diameter. Up to four sensor bodies can be configured as an evenly-spaced linear array. The sensor system operates by applying a low-frequency, current-stabilized, filtered triangle wave to a uniform-density excitation coil to switch the magnetic domains within the wire. Further, the responses from the sensors are picked up by a detection coil as stress-induced changes in the Faraday voltage, and the strong magnetic field induced by the excitation coil in the detection coil is nullified by a cancellation coil reverse-wound in series with the detection coil. The responses of the sensors in an array are separated in time by a linear gradient dc biasing coil. The sensors can be interrogated through metallic and nonmetallic barriers. The signals from the detection coil and the excitation coil are digitized by a pair of bipolar analog-to-digital converters (ADCs). A Raspberry Pi single-board computer (SBC) and associated software perform data acquisition and control all aspects of the sensor system hardware. The program allows the user to select the number of sensors in the array, the type of signal that is being collected, and the number of samples to take. The program also allows for signal processing of the sensor data, such as baseline correction. The program can differentiate sensor peaks from each other and calculate the magnitude of each sensor response with less than 1% error. The data are then displayed along with a graph of the signal.
One of the most common problems studied in the context of differential privacy for graph data is counting the number of non-induced embeddings of a subgraph in a given graph. These counts have very high global sensitivity. Therefore, adding noise based on powerful alternative techniques, such as smooth sensitivity and higher-order local sensitivity have been shown to give significantly better accuracy. However, all these alternatives to global sensitivity become computationally very expensive, and to date efficient polynomial time algorithms are known only for few selected subgraphs, such as triangles, k-triangles, and k-stars. In this paper, we show that good approximations to these sensitivity metrics can be still used to get private algorithms. Using this approach, we much faster algorithms for privately counting the number of triangles in real-world social networks, which can be easily parallelized. We also give a private polynomial time algorithm for counting any constant size subgraph using less noise than the global sensitivity; we show this can be improved significantly for counting paths in special classes of graphs
RTI Team, proposes an approach for demonstrating carbon-neutral methanol (MeOH) produced from carbon dioxide (CO 2 ) removed from air by direct air capture (DAC) and green hydrogen (H 2 ) from water (H 2 O) electrolysis using renewable electricity. The proposed project will include completing a feasibility study that informs a conceptual design of an integrated process that meets technical and economic targets set forth.
Effective and secure carbon subsurface storage, involving the deep underground injection of CO 2 into geological formations where it is permanently trapped, is paramount to mitigating CO 2 emissions (Figure I). Ensuring the integrity of these storage sites and detecting potential leakage through the casing annulus necessitates robust monitoring. This work provides the first integrated demonstration of a wireless casing-annulus monitoring architecture that can operate in highly attenuating cement-brine environments relevant to CO 2 storage. This project focused on developing and validating a novel sensor system for integration with autonomous monitoring near the cement reservoir interface. The goal was a fully integrated Technology Readiness Level (TRL) 4/5 field validation of a distributed wireless intelligent sensor system providing real-time, direct subsurface formation measurements to enhance fluid movement monitoring in the cemented casing annulus. Achieving this objective required the development and integration of 1) wireless autonomous microsensor technology by California Institute of Technology (Caltech); 2) sensor packaging and emplacement technology by Research Triangle Institute (RTI); and 3) smart well completions using wireless active casing collars and NOV pipe by the Sandia National Lab (SNL). The collaboration with the Caltech team in this project aimed to develop millimeter-scale radio frequency identification (RFID) sensors capable of detecting CO 2 , pH, and/or methane levels. These sensors are engineered to be impervious to fluids, allowing them to be mixed with cement and installed within the casing annulus. They operate using RFID protocols at frequencies of 902–928 MHz for both power and communication. A Sandia National Laboratories’ team engaged their expertise in the development of a Smart Collar system designed for the wireless data collection from these RFID sensors embedded in the cement annulus and transmission of this information to the ground surface via IntelliPipe/IntelliServ NOV drill pipe. This is accomplished through inductive coupling at the collar, which facilitates data transfer through each segment of the pipe. Because the system cannot transmit a direct current signal to power the Smart Collar, both power and communication were implemented using alternating current and electromagnetic signals at varying frequencies. Furthermore, the developed microsensor technology had to be demonstrated and validated in comparison with reference transducer measurements in a field test site at The University of Texas at Austin (UT-Austin). Although the full sensor suite did not reach field-deployment readiness, the system-level integration achieved in this project establishes a validated pathway for future incorporation of advanced microsensors.
Many countries, subnational jurisdictions, and companies are setting net-zero emissions goals; however, questions remain about strategies to reach these targets, policy measures, technology gaps, and economic impacts. Here, we investigate the potential policy implications of reaching economy-wide net-zero CO 2 emissions across the United States by 2050 using results from a multi-model comparison with 14 energy-economic models. Model results suggest that achieving net-zero CO 2 targets depends on policies that accelerate deployment of zero- and low-emitting technologies that have seen rapid cost reductions in recent years (including wind, solar, battery storage, and electric vehicles) as well as relatively nascent options (including carbon capture and storage, advanced biofuels, low-carbon hydrogen, advanced nuclear, and long-duration energy storage). While net-zero policies are likely to lower fossil fuel consumption, including considerable coal and petroleum reductions, achieving net-zero emissions does not necessarily mean phasing out all fossil fuels. Model results indicate that the Inflation Reduction Act’s energy and climate provisions amplify near-term decarbonization but that net-zero policies have larger impacts on long-run outcomes. Stringent climate policy can have large fiscal impacts on tax revenue and government spending—revenues from carbon pricing and subsidies for carbon removal range from 0.1 % to 3.7 % of GDP in 2050 across models. Each dollar per metric ton carbon price leads to a 0.06 % to 0.31 % reduction in economy-wide CO 2 emissions relative to a reference scenario with current policies. Spending on energy across the economy decreases relative to today for many models under reference and net-zero policies, especially as a share of GDP, due primarily to end-use electrification and energy efficiency.
Driven by the1.4 GW generator, the 60T Controlled Waveform (60 TCW) magnet was the most powerful controlled waveform system in the world and had always been one of most important magnets to the National High Magnetic Field (NHMFL) and high-field research community because of its following unique features: (1) quasi-static field up to 60 T with 100 ms flat-top and total pulse-length of about 2000 ms, (2) variable magnetic field waveforms such as staircase and triangle with flat-top (3) relative large bore (32 mm) and (4) very fast cooling time (20 minutes) between pulses [Boebinger, 2001], [Crooker et al. 2001]. The magnet is composed of nine concentric coils, with each coil consisting of several conductor winding layers reinforced by a high-strength metallic shell. The magnet underwent a catastrophic failure in 2000 and all the coils had to be rebuilt. In late 2014 the second magnet version failed near the mid-plane of coil 7. The simulations afterward that incident indicated that the overall strength of the coil would be increased by replacing a section of the reinforcing shell with Zylon fiber-epoxy composite. This reduces the stress and thus significantly lowers the level of plastic deformation in the windings. The role of the metal and Zylon fiber reinforcing layers in bearing the axial and radial Lorentz forces has been studied to optimize the magnet design. Here, the results of the optimization will be discussed as well as challenges that have been presented in rebuilding the individual coils of the magnet.