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At least 1,099 records · Page 61

Design and dispatch optimization of packaged ice storage systems within a connected community

The traditional implementation of cool thermal energy storage (CTES) must be reimagined within the context of a dynamic grid and smart buildings operating as connected communities. As most buildings do not operate central chillers or connect to district cooling loops, this necessitates a broader use of packaged CTES. Our objective is to begin answering the question of how such packaged CTES should be implemented within a connected community. We do so by presenting a simulation–optimization workflow employing building energy modeling software and a mixed-integer linear program to design and dispatch a packaged CTES technology to achieve minimum total annual cost. We demonstrate this methodology on a seven-building case study using current utility rates and find that total annual cooling energy costs can be reduced by 17.8% compared to baseline, after accounting for the cost of storage. We perform three parametric sensitivity studies to evaluate modeling assumptions and obtain the prioritization of storage procurement as a function of annualized life-cycle cost of storage. We find that a community optimization approach provides significantly different results than individual building optimizations and provides greater savings compared to baseline.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Proximity-induced magnetism and the enhancement of damping in ferromagnetic/heavy metal systems

The relationship between proximity-induced magnetism (PIM) at the heavy metal/ferromagnet interface and spin-transport across such interfaces has generated significant debate. To investigate the link between the two, element specific x-ray magnetic circular dichroism and ferromagnetic resonance measurements were made on the same CoFe/Au/Pt and NiFe/Au/Pt thin film samples with varying Au thickness, with complementary SIMS analysis, which shows evidence of Ni diffusion from NiFe into the Pt. An approximately linear relationship is observed between the magnitude of Pt PIM and magnitude of damping enhancement in both systems. The results demonstrate that electronic hybridization of the heavy metal and ferromagnet is required for a full understanding of damping enhancement and interfacial spintransport for spintronic devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Coupling Circularity With Carbon Negativity in Food and Agriculture Systems

Achieving a circular economy is critical for a sustainable future, particularly in sectors that currently produce resource-intensive products in a linear fashion, such as food and agriculture. At the same time, technologies that remove atmospheric CO 2 , often referred to as carbon dioxide removal (CDR) or carbon negativity, must be developed and deployed rapidly if we are to avoid the worst effects of climate change. Circularity and CDR are often assessed and discussed independently, even though they are highly intertwined. Innovations to food and agriculture systems are essential to achieving a circular economy and enabling rapid deployment of CDR technologies. We explore critical areas of technology that must undergo rapid innovation (upstream and downstream) to food processing and consumption, namely precision and regenerative agriculture and biorefining, respectively. If implemented at scale, these two areas of technology have the potential to couple circularity with carbon negativity in food production systems.

Biorefining↗

Probing Signal-Based Inertia and Frequency Response Estimation for Power Systems with High Penetration of Inverter-Based Resources: Preprint

Power system inertia is the inherent capability of a power system to resist changes in its frequency during disturbances. Real-time inertia estimation technology has become more important due to the low-inertia issues caused by the increasing integration levels of inverter-based resources (IBRs) from renewable energy; however, existing inertia estimation methods hardly consider multiple frequency response controls that act within the same time frame as conventional inertial response, thus making measured inertia values vary under different testing conditions. To resolve this issue, this paper proposes a novel real-time estimation method to simultaneously estimate a power system's inertia constant and frequency response droop constant using a well-designed probing signal. First, we formulate the inertia and frequency response model of a power system with IBRs. Second, through the integration and manipulation of the developed model, we propose a multivariate linear regression- based estimation method that is resilient to measurement noise. Third, we design a probing signal that can be injected by IBRs to incite the required transients for estimation. Finally, we validate the proposed estimation method through comprehensive power- hardware-in-the-loop experiments using inverter hardware and a realistic island power system model. The results demonstrate that the proposed method can accurately estimate the inertia and droop value of the power system with grid-following IBRs and grid-forming IBRs with virtual synchronous machine control.

frequency response↗

Decomposing Loosely Coupled Mixed-Integer Programs for Optimal Microgrid Design

Microgrids are frequently employed in remote regions, in part because access to a larger electric grid is impossible, difficult, or compromises reliability and independence. Although small microgrids often employ spot generation, in which a diesel generator is attached directly to a load, microgrids that combine these individual loads and augment generators with photovoltaic cells and batteries as a distributed energy system are emerging as a safer, less costly alternative. In this work, we present a model that seeks the minimum-cost microgrid design and ideal dispatched power to support a small remote site for one year with hourly fidelity under a detailed battery model; this mixed-integer nonlinear program (MINLP) is intractable with commercial solvers but loosely coupled with respect to time. A mixed-integer linear program (MIP) approximates the model, and a partitioning scheme linearizes the bilinear terms. We introduce a novel policy for loosely coupled MIPs in which the system reverts to equivalent conditions at regular time intervals; this separates the problem into subproblems that we solve in parallel. We obtain solutions within 5% of optimality in at most six minutes across 14 MIP instances from the literature and solutions within 5% of optimality to the MINLP instances within 20 minutes.

97 MATHEMATICS AND COMPUTING↗

Magnetic levitation

A magnetic levitation system is described, including a first cylinder-shaped magnet; a second cylinder-shaped magnet coaxially aligned with the first cylinder-shaped magnet; and a first cavity coaxially aligned with the first cylinder-shaped magnet; wherein the surfaces of the like-poles of the first and second cylinder-shaped magnets are parallel to each other and face each other to result in a linear magnetic field between the first and the second magnets. Methods of using a magnetic levitation system for analyzing a diamagnetic or paramagnetic sample are also described.

Ge, Shencheng↗

Probing Signal-Based Inertia and Frequency Response Estimation for Power Systems With High Levels of Inverter-Based Resources

Power system inertia is the inherent capability of a power system to resist changes in its frequency during disturbances. Real-time inertia estimation technology has become more important due to the low-inertia issues caused by the increasing integration levels of inverter-based resources (IBRs) from renewable energy; however, existing inertia estimation methods hardly consider multiple frequency response controls that act within the same time frame as conventional inertial response, thus making measured inertia values vary under different testing conditions. To resolve this issue, this paper proposes a novel real-time estimation method to simultaneously estimate a power system's inertia constant and frequency response droop constant using a well-designed probing signal. First, we formulate the inertia and frequency response model of a power system with IBRs. Second, through the integration and manipulation of the developed model, we propose a multivariate linear regression-based estimation method that is resilient to measurement noise. Third, we design a probing signal that can be injected by IBRs to incite the required transients for estimation. Finally, we validate the proposed estimation method through comprehensive power-hardware-in-the-loop experiments using inverter hardware and a realistic island power system model. The results demonstrate that the proposed method can accurately estimate the inertia and droop value of the power system with grid-following IBRs and grid-forming IBRs with virtual synchronous machine control.

frequency response↗

A General Autofluorescence Method to Characterize Polymerization Progress

Abstract An autofluorescence technique to characterize polymerization progress in real time/in line was developed, which functioned in the absence of typical fluorogenic groups on the monomer or polymer. The monomer dicyclopentadiene and polymer polydicyclopentadiene are hydrocarbons that lack traditional functional groups for fluorescence spectroscopy. Here, the autofluorescence of formulations containing this monomer and polymer during ruthenium‐catalyzed ring‐opening metathesis polymerization (ROMP) was harnessed for reaction monitoring. The methods fluorescence recovery after photobleaching (FRAP) and here‐developed fluorescence lifetime recovery after photobleaching (FLRAP) characterized polymerization progress in these native systems—without requiring exogenous fluorophore. (Auto)fluorescence lifetime recovery changes during polymerization correlated linearly to degree of cure, providing a quantitative link with reaction progress. These changing signals also provided relative rates of background polymerization, enabling comparison of 10 different catalyst‐inhibitor‐stabilized formulations. Multiple‐well analysis demonstrated suitability for future high‐throughput evaluation of formulations for thermosets. The central concept of the combined autofluorescence and FLRAP/FRAP method may be extendable to monitoring other polymerization reactions previously overlooked for lack of an obvious fluorescence handle.

López, Pía A.↗

A General Autofluorescence Method to Characterize Polymerization Progress

An autofluorescence technique to characterize polymerization progress in real time/in line was developed, which functioned in the absence of typical fluorogenic groups on the monomer or polymer. The monomer dicyclopentadiene and polymer polydicyclopentadiene are hydrocarbons that lack traditional functional groups for fluorescence spectroscopy. Here, the autofluorescence of formulations containing this monomer and polymer during ruthenium-catalyzed ring-opening metathesis polymerization (ROMP) was harnessed for reaction monitoring. The methods fluorescence recovery after photobleaching (FRAP) and here-developed fluorescence lifetime recovery after photobleaching (FLRAP) characterized polymerization progress in these native systems—without requiring exogenous fluorophore. (Auto)fluorescence lifetime recovery changes during polymerization correlated linearly to degree of cure, providing a quantitative link with reaction progress. These changing signals also provided relative rates of background polymerization, enabling comparison of 10 different catalyst–inhibitor-stabilized formulations. Multiple-well analysis demonstrated suitability for future high-throughput evaluation of formulations for thermosets. Furthermore, the central concept of the combined autofluorescence and FLRAP/FRAP method may be extendable to monitoring other polymerization reactions previously overlooked for lack of an obvious fluorescence handle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Designing Cyclic Nitrogen‐Bridged Sulfonamides with Anti‐Cancer Activity

The N-bridgehead heterocyclic structure is an abundant motif in a multitude of natural products. This structural feature is of high interest because it is present in many different bioactive molecules, many of which are well-established pharmaceuticals. The introduction of a sulfone group into the N-bridgehead system yields a new core structure containing a N-bridgehead sulfonamide. While linear sulfonamides can be found in natural products, only artificial cyclic sulfonamides are known to date. Applications of related cyclic sulfonamide compounds include matrix metalloproteinase inhibitors, potential HIV and cancer therapeutics, and anti-inflammatory compounds. To explore the potential bioactivity of the N-bridgehead sulfonamide scaffold, a synthetic route toward these scaffolds is developed and their bioactivity is explored against different cancer cell lines.

60 APPLIED LIFE SCIENCES↗

Impact of limestone fineness on cement hydration at early age

This study compares the influence of two limestone fineness on strength development and cement hydration. The replacement of clinker by 20% of fine limestone (d{sub v,50} = 2 μm and SSA = 4,21 m{sup 2}/g) gives similar strength development to PC up to 7 days. Fine limestone enhances cement hydration and offsets the dilution effect caused by the decrease of clinker amount. The accelerating effect of the limestone was explained by a higher degree of undersaturation with respect to C{sub 3}S. The influence of coarse limestone (d{sub v,50} = 130 μm and SSA = 0,46 m{sup 2}/g) on cement hydration is limited to dilution effect. The combination of fine and coarse limestone was also studied. A linear correlation was obtained between strength and gel space ratio for all investigated systems. Furthermore, the results showed that despite the similarity of specific surface area, limestone is more effective than quartz for the enhancement of cement hydration.

36 MATERIALS SCIENCE↗

CSPlib: A performance portable parallel software toolkit for analyzing complex kinetic mechanisms

Computational singular perturbation (CSP) is a method to analyze dynamical systems. It targets the decoupling of fast and slow dynamics using an alternate linear expansion of the right-hand side of the governing equations based on eigenanalysis of the associated Jacobian matrix. This representation facilitates diagnostic analysis, detection and control of stiffness, and the development of simplified models. For this work, we have implemented CSP in a C++ open-source library CSPlib using the Kokkos parallel programming model to address portability across diverse heterogeneous computing platforms, i.e., multi/many-core CPUs and GPUs. We describe the CSPlib implementation and present its computational performance across different computing platforms using several test problems. Specifically, we test the CSPlib performance for a constant pressure ignition reactor model on different architectures, including IBM Power 9, Intel Xeon Skylake, and NVIDIA V100 GPU. The size of the chemical kinetic mechanism is varied in these tests. As expected, the Jacobian matrix evaluation, the eigensolution of the Jacobian matrix, and matrix inversion are the most expensive computational tasks. When considering the higher throughput characteristic of GPUs, GPUs performs better for small matrices with higher occupancy rate. CPUs gain more advantages from the higher performance of well-tuned and optimized linear algebra libraries such as OpenBLAS.

97 MATHEMATICS AND COMPUTING↗

When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates

Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates. Our study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. We present and compare nine favorability maps for geothermal resources in the western United States using data from the U.S. Geological Survey's 2008 geothermal resource assessment. Two favorability maps are created using the expert decision-dependent methods from the 2008 assessment (i.e., weight-of-evidence and logistic regression). With the same data, we then create six different favorability maps using logistic regression (without underlying expert decisions), XGBoost, and support-vector machines paired with two training strategies. The training strategies are customized to address the inherent challenges of applying machine learning to the geothermal training data, which have no negative examples and severe class imbalance. We also create another favorability map using an artificial neural network. We demonstrate that modern machine learning approaches can improve upon systems built with expert decisions. We also find that XGBoost, a non-linear algorithm, produces greater agreement with the 2008 results than linear logistic regression without expert decisions, because the expert decisions in the 2008 assessment rendered the otherwise linear approaches non-linear despite the fact that the 2008 assessment used only linear methods. The F1 scores for all approaches appear low (F1 score < 0.10), do not improve with increasing model complexity, and, therefore, indicate the fundamental limitations of the input features (i.e., training data). Until improved feature data are incorporated into the assessment process, simple non-linear algorithms (e.g., XGBoost) perform equally well or better than more complex methods (e.g., artificial neural networks) and remain easier to interpret.

15 GEOTHERMAL ENERGY↗

Estimating the Electric Fields Driving Lightning Dart Leader Development With BIMAP‐3D Observations

Abstract In this paper, a numerical dart leader model has been implemented to understand the leader's development and the corresponding electric field changes observed by the 3D broadband mapping and polarization (BIMAP‐3D) system. The model assumes the extending leader channel is equipotential and has a linear charge distribution induced by an ambient electric field. The charge distribution induced by the ambient field can be used to model the electric field change at the ground. We then find the ambient electric field which best fits the field change measurements at the two BIMAP stations. The estimated ambient electric field decreases in the direction of dart leader propagation. Our observations and modeling results are consistent with our earlier hypothesis that dart leader speed is proportional to the electric field at the leader tip. The model also supports our earlier analysis that leader speed variations near branch junctions were due to previous charge deposits near the junctions. The modeled tip electric field is generally lower than the breakdown field unless the pre‐dart‐leader channel has a significant temperature of 3,000 K. This is consistent with the fact that dart leaders typically do not form new branches into the virgin air. Furthermore, the tip field is generally close to the negative streamer stability field at ambient temperatures, explaining the nature of the narrow and well‐defined channel structure. In addition to the charge distribution and the ambient and tip electric field, the development of the channel potential and current distribution are also presented.

3D lightning mapping↗

A linear response framework for quantum simulation of bosonic and fermionic correlation functions

Response functions are a fundamental aspect of physics; they represent the link between experimental observations and the underlying quantum many-body state. However, this link is often under-appreciated, as the Lehmann formalism for obtaining response functions in linear response has no direct link to experiment. Within the context of quantum computing, and via a linear response framework, we restore this link by making the experiment an inextricable part of the quantum simulation. This method can be frequency- and momentum-selective, avoids limitations on operators that can be directly measured, and can be more efficient than competing methods. As prototypical examples of response functions, we demonstrate that both bosonic and fermionic Green’s functions can be obtained, and apply these ideas to the study of a charge-density-wave material on the ibm_auckland superconducting quantum computer. The linear response method provides a robust framework for using quantum computers to study systems in physics and chemistry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Pseudospin-triplet pairing in iron-chalcogenide superconductors

Abstract Understanding the pairing symmetry is a crucial theoretical aspect in the study of unconventional superconductivity for interpreting experimental results. Here we study superconductivity of electron systems with both spin and pseudospin-1/2 degrees of freedom. By solving linearized gap equations, we derive a weak coupling criterion for the even-parity spin-singlet pseudospin-triplet pairing. It can generally mix with the on-site s -wave pairing since both of them belong to the same symmetry representation ( A 1 g ) and their mixture could naturally give rise to anisotropic intra-band pairing gap functions with or without nodes. This may directly explain why some of the iron-chalcogenide superconductors are fully gapped (e.g. FeSe thin film) and some have nodes (e.g. LaFePO and LiFeP). We also find that the anisotropy of gap functions can be enhanced when the principal rotation symmetry is spontaneously broken in the normal state such as nematicity, and the energetic stabilization of pseudospin-triplet pairings indicates the coexistence of nematicity and superconductivity. This could be potentially applied to bulk FeSe, where gap anisotropy has been experimentally observed.

Physics↗

Direct and rapid uranium isotopic analysis of environmental sample swipes via microextraction – LS-APGD/Orbitrap mass spectrometry

Accurate and precise isotopic analysis of actinides collected on environmental sample swipes from within nuclear facilities is an important safeguarding measure for detecting undeclared materials and activities. Traditional isotope ratio (IR) analysis of actinides using a bulk digestion approach can be laborious and time-consuming. Recently, direct analysis of environmental swipe samples using a microextraction approach has been explored as an alternative to conventional bulk digestion methods. The present study further evaluates this approach for accurate and precise isotopic analysis of uranium (U) in cotton swipe samples using the liquid sampling-atmospheric pressure glow discharge (LS-APGD)/Orbitrap-FTMS Booster detection system. The instrumental parameters were optimized, and quantitative capabilities were demonstrated through excellent linearity (R2 = 0.99) across a deposited mass range of 1 to 500 ng, with a limit of detection of 90 pg (in a 2 × 4 mm region) for total U; well below typical U concentrations (ng–mg range) in environmental sample swipes. The 235U/238U ratio showed excellent accuracy (−0.3% relative difference from the certificate value), with ∼20× improvement over previous microextraction-Orbitrap methods. Precision (∼1% relative standard deviation) was also greatly enhanced by ∼5×. This study also demonstrates that figures of merit achieved with neat U solution were not highly degraded when various external interfering elements/matrices were introduced. Finally, the developed method was successfully applied to analyze practical swipe samples representative of laboratory and outdoor environments. The presented figures of merit and applicability to practical samples further validate the capability of the platform for rapid analysis (<7 minutes) of environmental swipe samples.

Shrestha, Suraj [Clemson University, SC]↗

Disoriented isospin condensates in heavy-ion collisions

Anomalous neutral to charged kaon correlations measured by the ALICE collaboration have defied usual explanations. We propose that the large fluctuations could arise because of a disoriented isospin condensate where there is an imbalance between up and down condensates at the time kaons hadronize. This could happen in heavy-ion collisions when the quark condensate re-forms as the system cools and the approximate chiral symmetry of QCD is broken. Within the linear sigma model, we show that the energy cost of forming a disoriented isospin condensate is small making it very plausible.

Kapusta, Joseph [University of Minnesota, Minneapo↗