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At least 577 records · Page 32

A Two-Step Control Approach for Torque Ripple and Vibration Reduction in Switched Reluctance Motor Drives

The objective of this work is to reduce the torque ripple and vibration in Switched Reluctance Motor (SRM) drives. To achieve such a goal, a two-step approach is proposed. In the first step, the reference current is profiled using an optimization method, aimed to reduce the torque pulsation. In the second, the optimum current profile is applied to the SRM through an adaptive hysteresis band controller to actively cancel the radial vibration. The proposed technique uses an optimization procedure based on the Field Reconstruction Method (FRM) and Non-Derivative Optimization Method to find the optimal current profile that mitigates the torque pulsation, however, the investigation has shown that the proposed excitation leads to a higher radial vibration, which has been mitigated by using an adaptive hysteresis band controller. The theoretical basis for the proposed approach is initially presented, followed by system modeling and simulation. In addition, experimental verification has been conducted using an 8/6 SRM to show the feasibility of the proposed approach. The proposed method alleviates the acoustic noise and torque pulsation in SRM and offers an effective step towards the prevalent use of SRM in a wide range of applications.

42 ENGINEERING↗

Optimization of Graphite–SiO blend electrodes for lithium-ion batteries: Stable cycling enabled by single-walled carbon nanotube conductive additive

Lithium-alloying materials are of great interest to improve the gravimetric and volumetric energy density of lithium-ion batteries, though their associated volume fluctuation with cycling often leads to poor cycling performance. Active-inactive alloys and blending alloys with carbon materials are common strategies to accommodate volume fluctuation. Herein we set out to optimize graphite-SiO blend electrode formulations to eliminate rapid capacity fade. Electrodes with highly stable cycling were prepared by simple planetary mixing procedures, enabled by the use of just a fraction of a weight percent of commercial SWCNTs as the only conductive additive, and by the appropriate choice of binder/stabilizing agent. In fact, the use of SWCNTs allowed for graphite-free SiO electrodes with approximately 74% higher volumetric energy density relative to traditional graphite electrodes, and superior capacity retention in coin-type full-cell testing versus NMC532 cathodes.

25 ENERGY STORAGE↗

Leveraging Stereochemistry to Optimize the Properties of Polyhydroxyalkanoates

The recycling of low-density polyethylene (LDPE) is challenging due to difficulties with sorting and contamination, leading to environmental harm. Polyhydroxyalkanoates (PHAs) are at the forefront of high-performance biodegradable alternatives to olefinic plastics, but few offer LDPE-like properties such as low strength and crystallinity while maintaining high ductility and thermal stability. Herein, we report a series of isoenriched transpoly( 3-hydroxy-2-methylbutyrates) (trans-PHMBs) with tunable mechanical and thermal properties. These polymers were synthesized through ring-opening polymerization of racemic trans-3,4-dimethylpropiolactone (rac-trans-DMPL), sourced from C1 and C4 feedstocks, using a new class of “sandwich” C 2 symmetric rac-( Ar BDI*)ZnO i Pr catalysts (where BDI = β-diketiminate). Variation of aromatic groups (Ar) and polymerization temperature yielded mm%s between 45−79% and melting temperatures (T m ) between 141−174 °C. trans-PHMB with intermediate isotacticities of 73 and 75 mm% exhibit similar stress−strain profiles to LDPE, indicating that these polymers have the potential to serve as higher melting, degradable substitutes for LDPE.

Biopolymers↗

A machine learning framework for accurate and robust analysis of radiation detector pulses

The microscopic properties of atomic nuclei are used to study various scientific questions. They are essential for understanding the fundamental forces of nature and the chemical evolution of the universe. Detecting decay radiation from radioactive nuclei makes it possible to probe these fundamental nuclear properties. Detector waveform traces may contain additional information about the radiation. Generally, advanced signal processing techniques are needed to extract this additional information, often involving fitting the waveform with model response functions using non-linear least-squares optimization with second-order gradient methods. While this is a powerful technique, it is also computationally expensive, leading to slow processing time, which scales with the volume of data. To address this problem, we have developed a machine learning (ML) approach that infers the characteristics of traces from a model detector response function. In particular, we are interested in classifying whether a single recorded trace consists of one or two pulse constituents and estimating the pulse parameters. Furthermore, our proposed ML method can precisely extract the pulses’ parameters, such as energy and timing information, and accurately classify the pulse multiplicity of a trace. Unlike non-learning-based approaches, our ML approach uses neural networks that are significantly faster at inference, as they do not require any optimization during this stage.

Curve fitting↗

Optimization of the N ∥ Upshift in the DIII-D high field side lower hybrid current drive experiment

High field side lower hybrid current drive (LHCD) is one potential candidate for efficient non-inductive current drive in tokamak power plants, and the first test of this technology will occur on the DIII-D tokamak during the 2024 campaign. Previous LFS launch experiments operated in the multi-pass regime and relied on scrape-off layer interactions to close the spectral gap. In the DIII-D experiment, single-pass damping is achievable via an upshift in the parallel refractive index N ∥ caused by mode converting twice (slow → fast → slow). This mode conversion affects the ray trajectories and can lead to enhanced N ∥ upshift depending on where mode conversion occurs. Compared to multi-pass absorption experiments, the optimization of launched N ∥ and plasma parameters can be counter-intuitive: increased density may increase efficiency and smaller N ∥,launch tend to damp closer to the separatrix. A hard x-ray camera installed to measure the bremsstrahlung (50–250 keV) radiation from LHCD-generated fast electrons is capable of verifying the trends reporting in this paper through comparison to the ray-tracing/Fokker–Planck codes GENRAY/CQL3D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Diagnosing Barren Plateaus with Tools from Quantum Optimal Control

Variational Quantum Algorithms (VQAs) have received considerable attention due to their potential for achieving near-term quantum advantage. However, more work is needed to understand their scalability. One known scaling result for VQAs is barren plateaus, where certain circumstances lead to exponentially vanishing gradients. It is common folklore that problem-inspired ansatzes avoid barren plateaus, but in fact, very little is known about their gradient scaling. In this work we employ tools from quantum optimal control to develop a framework that can diagnose the presence or absence of barren plateaus for problem-inspired ansatzes. Such ansatzes include the Quantum Alternating Operator Ansatz (QAOA), the Hamiltonian Variational Ansatz (HVA), and others. With our framework, we prove that avoiding barren plateaus for these ansatzes is not always guaranteed. Specifically, we show that the gradient scaling of the VQA depends on the degree of controllability of the system, and hence can be diagnosed through the dynamical Lie algebra $\mathfrak{g}$ obtained from the generators of the ansatz. We analyze the existence of barren plateaus in QAOA and HVA ansatzes, and we highlight the role of the input state, as different initial states can lead to the presence or absence of barren plateaus. Taken together, our results provide a framework for trainability-aware ansatz design strategies that do not come at the cost of extra quantum resources. Moreover, we prove no-go results for obtaining ground states with variational ansatzes for controllable system such as spin glasses. Our work establishes a link between the existence of barren plateaus and the scaling of the dimension of $\mathfrak{g}$.

97 MATHEMATICS AND COMPUTING↗

Liquid-Cooled Heat Sink Optimization for Thermal Imbalance Mitigation in Wide-Bandgap Power Modules

Power semiconductor die layout in substrates used in power modules is generally optimized for minimum electrical parasitics (e.g., stray inductance) by considering the minimum spacing between dies for thermal decoupling. The layout assumes sufficient heat spreading and transfer from dies to the cooling structure. For module designs using a direct substrate cooling method, the base plate is removed, leading to a steady-state thermal asymmetry in the power module due to insufficient heat spreading/transfer. This causes significant temperature differences among the devices. Such unintentional thermal asymmetries can lead to undesirable asymmetries in power conversion among semiconductor devices, which impact reliability. This article proposes a thermal imbalance mitigation method that uses evolutionary optimized liquid-cooled heat sinks to improve the thermal loading among devices.

Sahu, Raj↗

Advances in laser-based bremsstrahlung x-ray sources. I. Optimizing laser-accelerated electrons

In this work, we have performed a suite of kinetic simulations of relativistic laser–plasma interaction under settings relevant to recent and planned experiments on a variety of laser systems. The goal of the study is to illuminate the physics of laser–target coupling and to provide guidance for how to optimize these sources for applications. It is shown that the production of relativistic electrons is maximized when conditions of relativistic induced transparency (RIT) in dense plasmas can be achieved over a large interaction volume at the time of arrival of most intense part of the laser pulse. RIT is shown to enhance both the numbers of relativistic electrons and the energies of the electrons, leading to an increased x-ray dose. A variety of approaches to enhancing laser–target coupling are considered. These include optimizing the effects of low-density pre-plasma (arising either from finite laser pedestal or from the use of foam coatings) and of modifying the laser focusing geometry to reduce effects of filamentation and self-focusing. Evidence of a novel approach to achieving stable laser propagation over distances of tens of micrometers in a plasma gradient is also presented. These conditions coincide with plasma and laser conditions explored in recent experiments on the Omega EP laser system and compare favorably with an analytic criterion for stable laser propagation in relativistically underdense plasma obtained from a nonlinear Wentzel–Kramers–Brillouin analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimal Distribution System Voltage Regulation using State Estimation and DER Grid-Support Functions

Increasing solar energy penetrations may create challenges for distribution system operations because production variability can lead to large voltage deviations or protection system miscoordination. Instituting advanced management systems on distribution systems is one promising method for combating these challenges by intelligently controlling distribution assets to regulate voltage and ensure protection safety margins. While it is generally not the case today, greater deployment of power system sensors and interoperable distributed energy resources (DER)e.g., photovoltaic (PV) inverters, energy storage systems (ESS), electric vehicles (EVs)will enable situational awareness, control, and optimization of distribution systems. In this work, a control system was created which measures power system parameters to estimate the status of a feeder, forecasts the distribution state over a short-term horizon, and issues optimal set point commands to distribution-connected equipment to regulate voltage and protect the system. This two-year project integrated multiple research innovations into a management system designed to safely allow PV penetrations of 50% or greater. The integrated software was demonstrated through extensive real-time (RT) and power hardware-in-the-loop studies and a field demonstration on a live power system with a 684 kVA PV system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Systems Analysis and Optimization of Circular PET Packaging Supply Chains in the United States: Environmental and Socioeconomic Impacts

Many actions are underway at global, national, and local levels to address the plastic waste problem and transition toward a circular economy of plastics. Studies evaluating environmental and socioeconomic impacts of such a transition are lacking. Here, the purpose of this study is to conduct a national systems analysis of polyethylene terephthalate (PET) packaging supply chains in the United States. Material flow data was combined with environmental and socioeconomic indicators to evaluate and compare the sustainability of the linear PET packaging supply chain, current (2019) supply chain, and possible future circular supply chain options in the United States. Environmentally optimal circular US PET packaging material flows showed 31% and 38% savings of GHG emissions and energy demand, respectively, with a circularity of 77% when compared with a linear supply chain. Additionally, the environmentally optimal system showed higher employment (29%) and wages (31%) than a linear system, but with a 5% decrease in revenue generation. A socioeconomically optimal circular PET supply chain showed increased employment (by 52%), wages (by 67%), and revenues (by 1%), with a circularity of 59% when compared with the linear system. However, it showed 14% higher GHG emissions than a linear system, indicating a trade-off between environmentally and socioeconomically optimal circular PET packaging systems. Overall, linear-to-circular material flow transition may not necessarily lead to increased revenues and decreased environmental impacts of the entire system, but it does benefit society due to increased employment and wages. Future systems analysis work should focus on improving data quality for environmental and socioeconomic dimensions.

PET↗

High protonic resistance of hydrocarbon-based cathodes in PEM fuel cells under low humidity conditions: Origin, implication, and mitigation

Hydrocarbon-based electrodes for proton-exchange membrane fuel cells face challenges in closing the performance gap with electrodes based on perfluorosulfonic acid ionomers, particularly under low humidity conditions. Alongside increased oxygen transport resistance and higher kinetic-induced overpotentials, the protonic resistance of these fluorine-free electrodes is the primary hurdle to improved performance. This study systematically investigates the origin and impact of the cathode protonic resistance on fuel cell performance, utilizing sulfonated phenylated polyphenylenes as hydrocarbon ionomers. Electrochemical characterization at low relative humidity (≤50 %) reveal a high protonic resistance arising from both lower conductivity of the hydrocarbon thin film compared to the bulk membrane and increased cathode tortuosity at a gas transport-optimized ionomer to carbon (I/C) ratio of 0.2. The poor protonic resistance at low relative humidities leads to a non-homogeneous current distribution across the thickness of the cathode electrode, resulting in lower catalyst utilization. To address this issue, reducing the thickness of the cathode CL while maintaining a constant Pt loading (i.e., increasing the Pt on carbon ratio) significantly reduces protonic resistance. This improvement compensates for the kinetic disadvantages of highly loaded carbon particles and results in a considerable performance increase by 40 % at 0.75 V under low relative humidities.

25 ENERGY STORAGE↗

Transient fuel performance analysis for the preliminary fuel concept of general atomics fast modular reactor

This study investigates the transient fuel performance of General Atomics Fast Modular Reactor (GA-FMR) during accident scenarios, focusing on the behavior of its innovative fuel system that combines high-assay low enriched uranium dioxide (HALEUO2) fuel with SiGA® ceramic matrix composite silicon carbide cladding. The preliminary fuel design’s response was analyzed during reactivity-initiated accidents (RIA) and loss of coolant accidents (LOCA) using BISON fuel performance analysis code, which included both the diffusion enhanced and BISON-FASTGRASS coupled UO 2 models. The RIA analysis demonstrated that effective reactivity control reduced fuel temperature, though with transient fission gas release resulting in additional tensile stress state on the cladding. LOCA simulations revealed differing predictions between the two models: the BISON UO 2 model showed more transient fission gas release but minimal pellet expansion, while the BISON-FASTGRASS UO 2 model predicted less pronounced fission gas release but more fuel swelling and thermal expansion, potentially leading to pellet-cladding mechanical interaction. Here, these findings highlight critical areas for fuel design optimization and identify knowledge gaps requiring further experimental and computational investigation to advance GA-FMR fuel development.

Lee, Soon K. [Argonne National Laboratory (ANL), A↗

Encumbering the Copper(I)-Diimine Coordination Sphere with a Benzyl Group: Impact on the Stability and Photoredox Properties

Copper(I)-bisdiimine complexes, [Cu(NN) 2 ] + (where NN represents a diimine such as phenanthroline or bipyridine derivatives), are considered promising photosensitizers for various photochemical applications. However, their effectiveness is subject to several key challenges. In particular, controlling steric strain around the copper(I) center by introducing appropriate substituents (R) at the α-position of the nitrogen atoms is crucial for optimizing the excited-state properties of the complex. In brief, increasing the size of R leads to longer emission lifetimes and higher quantum yields. Additionally, the energy of the singlet excited state rises with increasing steric bulk, enhancing photoinduced reactivity. However, excessive steric strain from bulky substituents can significantly destabilize the coordination sphere. To balance complex stability with increased steric bulk around the metal center, we have developed two novel non-symmetrical ligands featuring branched alkyl chains and benzyl groups at the α-position of the nitrogen atoms. Here, our findings demonstrate that intramolecular π-stacking interactions between the benzyl group and the opposing phenanthroline ligand contribute to stabilizing the coordination sphere. Furthermore, the flexibility of the benzyl group reinforces the tetrahedral geometry around copper(I), resulting in an increased singlet excitedstate energy compared to benchmark complexes. Notably, we show that this enhancement in excited-state energy translates into greater excited-state reactivity.

Copper(I)↗

How machine learning can help select capping layers to suppress perovskite degradation

Environmental stability of perovskite solar cells (PSCs) has been improved by trial-and-error exploration of thin low-dimensional (LD) perovskite deposited on top of the perovskite absorber, called the capping layer. In this study, a machine-learning framework is presented to optimize this layer. We featurize 21 organic halide salts, apply them as capping layers onto methylammonium lead iodide (MAPbI 3 ) films, age them under accelerated conditions, and determine features governing stability using supervised machine learning and Shapley values. We find that organic molecules’ low number of hydrogen-bonding donors and small topological polar surface area correlate with increased MAPbI 3 film stability. The top performing organic halide, phenyltriethylammonium iodide (PTEAI), successfully extends the MAPbI3 stability lifetime by 4 ± 2 times over bare MAPbI 3 and 1.3 ± 0.3 times over state-of-the-art octylammonium bromide (OABr). Through characterization, we find that this capping layer stabilizes the photoactive layer by changing the surface chemistry and suppressing methylammonium loss.

36 MATERIALS SCIENCE↗

Organizing principles for vegetation dynamics

Understanding vegetation dynamics is very challenging because of the multitude of contributing processes at 64widely different spatial and temporal scales. In this Perspective we propose that understanding of vegetation dynamics can be improved, permitting better predictions, based on organizing principles that constrain plant and ecosystem be haviour: natural selection, self-organization, and entropy maximization. Although these ideas are increasingly used,a limited common understanding of their theoretical basis has prevented their full potential to be realized. We explain the power of natural selection-based optimality to predict photosynthesis and carbon allocation responses to multiple environmental drivers, and how individual plasticity leads to the predictable self-organization of forest canopies. We show how models of natural selection acting on a few key traits can generate realistic plant communities, and how entropy maximization can distinguish between stochastic and deterministic drivers of vegetation patterns. In combination with empirical exploration of patterns in plant functional variation, these principles can accelerate the development of dynamic vegetation models as well as trait-based ecology resting on strengthened theoretical and empirical foundations.

Geosciences↗

Model predictive control for voltage restoration in microgrids using temporal logic specifications

Power system operation will encounter numerous voltage variabilities as the proliferation of renewable energy continues. Real-time monitoring and communication technologies can potentially improve voltage stability by enabling the rapid detection of voltage deviations and the implementation of corrective actions. These corrective actions will only be effective in restoring stability if they are chosen in a timely and scalable manner. This paper considers the problem of power systems’ load voltage control in order to simultaneously address both magnitude and time voltage specifications. In order to comply with grid codes and avoid unnecessary relay protection actions, a model predictive control (MPC)-based control strategy employing temporal logic specifications (TLSs) is proposed. The TLSs strategy is introduced as a formalism to control the voltage variation at a critical load bus against operational bounds over time. The control objective is to schedule optimal control input signals from the available supportive energy storage systems, which provide reactive power injections, leading to satisfying the specified finite-time restoration described by the TLSs with minimal control efforts. The simulation results display that the TLSs strategy for power systems’ voltage control synthesis is extremely significant.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A cautionary tale: Problems in the valence-CASSCF description of the ground state (X1Σ+) of BF

In the full optimized reaction space and valence-complete active space self-consistent field (vCAS) methods, a set of active orbitals is defined as the union of the valence orbitals on the atoms, all possible configurations involving the active orbitals are generated, and the orbitals and configuration coefficients are self-consistently optimized. Such wave functions have tremendous flexibility, which makes these methods incredibly powerful but can also lead to inconsistencies in the description of the electronic structure of molecules. In this paper, the problems that can arise in vCAS calculations are illustrated by calculations on the BH and BF molecules. BH is well described by the full vCAS wave function, which accounts for molecular dissociation and 2s–2p near-degeneracy in the boron atom. The same is not true for the full vCAS wave function for BF. There is mixing of core and active orbitals at short internuclear distances and swapping of core and active orbitals at large internuclear distances. In addition, the virtual 2π orbitals, which were included in the active space to account for the 2s–2p near degeneracy effect, are used instead to describe radial correlation of the electrons in the F2pπ-like pairs. Although the above changes lead to lower vCAS energies, they lead to higher vCAS+1+2 energies as well as irregularities and/or discontinuities in the potential energy curves. All of the above problems can be addressed by using the spin-coupled generalized valence bond-inspired vCAS wave function for BF, which includes only a subset of the atomic valence orbitals in the active space.

Xu, Lu T. (ORCID:0000000182064902)↗