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At least 19 records

Propulsion system sizing for powered lift and mechanical flap quiet aircraft

A method of propulsion system sizing for mechanical flap and externally blown flap aircraft is demonstrated. Included in this study is the effect of various levels of noise suppression on the aircraft final design characteristics. Both aircraft are sized to operate from a 3000-ft runway and perform the same mission. For each aircraft concept, propulsion system sizing is demonstrated for two different engine cycles - one having a fan pressure ratio of 1.5 and a bypass ratio of 9 and the other having a fan pressure ratio of 1.25 and a bypass ratio of 17.8. The results presented include the required thrust to weight ratio and wing loading and the resulting gross weight and direct operating costs as functions of the engine noise level for each of the four combinations of engine cycles and aircraft concepts.

Bowles, J. V.

A high resolution holographic particle sizing system

This paper will review briefly the requirements of holography with respect to particle sizing techniques. A holographic construction system and the appropriate reconstruction system will be discussed regarding their characteristics and performance (i.e. system resolution, magnification, system aberration and correction of aberrations, and maximum total test volume). The capabilities of a commercial particle sizing system used to obtain particle sizes and distribution information from reconstructed holograms will be described and characterized. It will be shown that by using the methods described, high resolution throughout large test volumes can be achieved.

Witherow, W. K.

Similarity for downscaled kinetic simulations of electrostatic plasmas: Reconciling the large system size with small Debye length

A simple similarity has been proposed for kinetic (e.g., particle-in-cell) simulations of plasma transport that can effectively address the long-standing challenge of reconciling the tiny Debye length with the vast system size. This applies to both transport in unmagnetized plasma and parallel transport in magnetized plasmas, where the characteristics length scales are given by the Debye length, collisional mean free paths, and the system or gradient lengths. The controlled scaled variables are the configuration space, x/L, and an artificial Coulomb Logarithm, L ln Λ, for collisions, while the scaled time, t/L, and electric field, LE, are automatic outcomes. The similarity properties are examined, demonstrating that the macroscopic transport physics is preserved through a similarity transformation while keeping the microscopic physics at its original scale of Debye length. To showcase the utility of this approach, two examples of 1D plasma transport problems were simulated using the VPIC code: the plasma thermal quench in tokamaks [Li et al., Nuclear Fusion 63, 066030 (2023)] and the plasma sheath in the high-recycling regime [Li et al., Physics of Plasmas 30, 063505 (2023)].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

System-size dependence of charged-particle suppression in ultrarelativistic nucleus-nucleus collisions

High-energy partons lose energy while propagating through the hot, strongly interacting medium produced in ultrarelativistic nucleus-nucleus collisions, leading to a suppression of particle production at high transverse momentum (p T ). The dependence of this energy loss on the size of the colliding nuclear system has yet to be firmly established experimentally. This Letter presents a systematic study of charged-particle suppression across four different nucleus-nucleus collision systems using nuclear modification factors (R AA ) measured by the CMS Collaboration at the CERN LHC. Previous CMS measurements of R AA in oxygen-oxygen, xenon-xenon, and lead-lead collisions are recast with identical p T intervals and are complemented by the first measurement of the charged-particle R AA in neon-neon collisions at $\sqrt{S_{NN}}$ = 5.36 Te V . The neon-neon data correspond to an integrated luminosity of 0.76 nb −1 . The R AA in all collision systems examined show similar qualitative trends as a function of p T , but have a magnitude which is ordered with the nucleon number A. The R AA feature a downward slope at low p T , a local minimum at around 5–7 Ge V , and an upward slope with increasing p T . The R AA are also compared in terms of A 1/3 , which is proportional to the nuclear radius. Models including only initial-state nuclear effects fail to reproduce the observed trends, whereas energy loss models reproduce the trends in the region p T > 9.6 Ge V .

CMS

Smaller SPS system sizing tradeoffs

The solar power satellite and associated microwave system was reoptimized with larger antennas (at 2.45 GHz), reduced output powers, and smaller rectennas. Four constraints were considered: (1) the 23 mw/sq cm ionospheric limit; (2) a higher (54 mW/sq cm) ionospheric limit; (3) the 23 KW/sq cm thermal limit in the antenna; and (4) an improved thermal design allowing 33% additional waste heat. The differential costs in electricity for seven antenna/rectenna configurations operating at 2.45 GHz and five satellite systems operating at 5.8 GHz were calculated. It is concluded that a larger antenna/smaller rectenna configurations are economically feasible under certain conditions; a transmit antenna diameters should be limited to 1 to 1.5 Km for 2.45 GHz operation and .75 to 1.0 Km for 5.8 GHz; the present ionospheric limit of 23 mw/sq cm is probably too low and should be raised after ionospheric heating tests and studies are completed; the 5.8 GHz configurations are constrainted by antenna thermal limitations, rather than ionospheric limits; and multiple (two to four) antennas on a single solar satellite are recommended regardless of the particular antenna/rectenna configuration chosen.

Arndt, G. D.

Solar power satellite system sizing tradeoffs

Technical and economic tradeoffs of smaller solar power satellite systems configured with larger antennas, reduced output power, and smaller rectennas, are considered. The differential costs in electricity for seven antenna/rectenna configurations operating at 2.45 GHz and five satellite systems operating at 5.8 GHz are calculated. Two 2.45 GHz configurations dependent upon the ionospheric power density limit are chosen as examples. If the ionospheric limit could be increased to 54 mW sq/cm from the present 23 mW sq/cm level, a 1.53 km antenna satellite operating at 2.45 GHz would provide 5.05 GW of output power from a 6.8 km diameter rectenna. This system gives a 54 percent reduction in rectenna area relative to the reference solar power satellite system at a modest 17 percent increase in electricity costs. At 5.8 GHz, an 0.75 km antenna providing 2.72 GW of power from a 5.8 km diameter rectenna is selected for analysis. This configuration would have a 67 percent reduction in rectenna area at a 36 percent increase in electricity costs. Ionospheric, atmospheric, and thermal limitations are discussed. Antenna patterns for three configurations to show the relative main beam and sidelobe characteristics are included.

Arndt, G. D.

Influence of propulsion system size, shape, and location on supersonic aircraft design

The effects of various propulsion system parameters on the characteristics of a supersonic transport were investigated. The effects of arbitrarily scaling engine size on wave drag, friction drag, drag-due-to-lift, wing sizing, airplane balance, and airplane weight were studied. These evaluations were made for two families of nacelle shapes, resulting from typical turbojet and turbofan installations. Also examined were effects of nacelle location, and the wing camber plane deformations required to cancel the nacelle interference pressure field at cruise Mach number (2.7 M) were determined. The most drag-sensitive parameter is found to be nacelle shape. Similarly, wing deformation requirements are found to be primarily affected by nacelle shape. Effects of engine size variations are noted primarily in airplane gross weight.

Bonner, E.

System size and energy dependence of the mean transverse momentum fluctuations at the LHC

Event-by-event fluctuations of the event-wise mean transverse momentum, $\langle$p T $\rangle$, of charged particles produced in proton–proton (pp) collisions at $\sqrt{s}$ = 5.02 TeV, Xe–Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV, and Pb–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV are studied using the ALICE detector based on the integral correlator $\langle$$\langle$Δp T Δp T $\rangle$$\rangle$. The correlator strength is found to decrease monotonically with increasing produced charged-particle multiplicity measured at midrapidity in all three systems. In Xe–Xe and Pb–Pb collisions, the multiplicity dependence of the correlator deviates significantly from a simple power-law scaling as well as from the predictions of the HIJING and AMPT models. The observed deviation from power-law scaling is expected from transverse radial flow in semicentral to central Xe–Xe and Pb–Pb collisions. In pp collisions, the correlation strength is also studied by classifying the events based on the transverse spherocity, S 0 , of the particle production at midrapidity, used as a proxy for the presence of a pronounced back-to-back jet topology. Low-spherocity (jetty) events feature a larger correlation strength than those with high spherocity (isotropic). The strength and multiplicity dependence of jetty and isotropic events are well reproduced by calculations with the PYTHIA 8 and EPOS LHC models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

An Anisotropic Yield and Damage Material Model to Improve the Contact Pressure Analysis in a Biomass Shredding System

Size reduction systems used in biomass processing break biomass into smaller pieces by utilizing the kinetic energy from the sharp rotating blades. Abrasive and/or erosive wear caused by biomass comminution results in blade wear of the sharp edged cutters, deteriorating the process efficiency. Here, this study aims to optimize the blade design and improve the system efficiency by attempting to understand the interactions between the blades and biomass particles. Since real-time monitoring of these interactions is impractical during operation, mechanical simulations offer a viable alternative for investigating the shredding process. Yet, the irregular geometry and complex mechanical properties of biomass—such as the anisotropic nature of woodchips and their nonlinear fracture behavior—pose significant challenges for accurately simulating contact pressure. In this work an anisotropic yield material model, along with a damage initiation and evolution function, is applied to the woodchip particle to study the contact pressure on shredder blade, offering a scientific basis for improved blade design and process efficiency. This approach can be extended to other biomass processing systems with similar anisotropic feedstocks, making it a valuable tool for advancing sustainable biomass utilization.

09 - BIOMASS FUELS

Optimal sizing of battery energy storage systems for peak shaving and demand response using a degradation-aware Bayesian Optimization-Mixed-Integer Linear Programming framework

The increasing integration of renewable energy and rising electricity demand highlight the importance of battery energy storage systems for peak shaving and demand response. Unlike prior approaches that overlook operational impacts on degradation, this study proposes a Bayesian Optimization–Mixed Integer Linear Programming framework for optimal battery energy storage system sizing. In this framework, Mixed Integer Linear Programming determines short-term scheduling while a calibrated electrochemical model iteratively evaluates degradation. The central hypothesis is that the framework can efficiently identify optimal sizes that yield realistic and economically robust outcomes. The method is tested across three scenarios: peak shaving, peak shaving with energy-reduction demand response, and peak shaving with power-reduction demand response. Results show that the framework converge to the optimum within 20 iterations out of 150 possible sizes. Under baseline conditions, the framework consistently selects the smallest feasible system, minimizing unnecessary degradation costs from oversized storage. Sensitivity analyses reveal that larger systems are favored as demand rates or incentives increase. Comparisons of demand response programs indicate that power-reduction demand response offers greater economic benefits than energy-reduction demand response, although demand savings from peak shaving remain the dominant contributor to overall performance. This study demonstrates that the proposed framework balances computational tractability with degradation fidelity, identifies critical economic thresholds for investment, and offers a practical, flexible tool to guide industrial stakeholders in cost-effective battery energy storage system deployment.

Batteries

Rapid Quantum Ground State Preparation via Dissipative Dynamics

Inspired by natural cooling processes, dissipation has become a promising approach for preparing low-energy states of quantum systems. However, the potential of dissipative protocols remains unclear beyond certain commuting Hamiltonians. This work provides significant analytical and numerical insights into the power of dissipation for preparing the ground state of noncommuting Hamiltonians. For quasi-free dissipative dynamics, including certain 1D spin systems with boundary dissipation, our results reveal a new connection between the mixing time in trace distance and the spectral properties of a non-Hermitian Hamiltonian, leading to an explicit and sharp bound on the mixing time that scales polynomially with system size. For more general spin systems, we develop a tensor network-based algorithm for constructing the Lindblad jump operator and for simulating the dynamics. Using this algorithm, we demonstrate numerically that dissipative ground state preparation protocols can achieve rapid mixing for certain 1D local Hamiltonians under bulk dissipation, with a mixing time that scales logarithmically with the system size. We then prove the rapid mixing result for certain weakly interacting spin and fermionic systems in arbitrary dimensions, extending recent results for high-temperature quantum Gibbs samplers to the zero-temperature regime. Together, these results show that dissipation can be a powerful tool for ground state preparation, with potential applications across condensed matter physics, quantum materials science, and beyond.

decoherence

Efficient quantum circuits based on the quantum natural gradient

Efficient preparation of arbitrary entangled quantum states is crucial for quantum computation. This is particularly important for noisy intermediate-scale quantum simulators relying on variational hybrid quantum-classical algorithms. To that end, we propose symmetry-conserving modified quantum approximate optimization algorithm (SCom-QAOA) circuits. The depths of these circuits depend not only on the desired fidelity to the target state but also on the amount of entanglement the state contains. The parameters of the SCom-QAOA circuits are optimized using the quantum natural gradient method based on the Fubini-Study metric. The SCom-QAOA circuit transforms an unentangled state into a ground state of a gapped one-dimensional Hamiltonian with a circuit depth that depends not on the system size but rather on the finite correlation length. In contrast, the circuit depth grows proportionally to the system size for preparing low-lying states of critical one-dimensional systems. Even in the latter case, SCom-QAOA circuits with depth less than the system size were sufficient to generate states with fidelity in excess of 99%, which is relevant for near-term applications. The proposed scheme enlarges the set of the initial states accessible for variational quantum algorithms and widens the scope of investigation of nonequilibrium phenomena in quantum simulators. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Advancing Our Understanding of System Availability through the PV Fleet Performance Data Initiative

The PV Fleet Performance Data Initiative partners with photovoltaic (PV) fleet owners to collect time-series data of PV production data and publishes aggregated anonymized results of system performance metrics. With an extensive dataset drawn from over 2,200 PV systems across the United States, comprising 8.5 GW and 24,000 separate inverter data channels, this initiative aims to ensure that systemic risks in the US PV fleet are detected. The current work explores system availability, revealing a pronounced dependence on time, especially within the initial 6 months of system performance. Following this start-up period, the average system availability stabilizes. Statistical analyses illustrate a median (P5O) monthly availability of 0.991 and a dependence on system size with a negative trend in availability with increasing system size. This finding indicates that larger systems experience lower availability compared to their smaller counterparts.

inverter availability

Queueing analysis of synchronous time division multiplexing with individual source buffering

Synchronous time division multiplexing is analyzed. Packets of information arrive at the system as a compound Poisson process, and are transmitted only during individual periodic intervals. Packet arrivals are blocked (lost) if the system has a finite capacity and is congested. Using the theory of semiregenerative processes, the distribution of the number of packets in the system (system size) is found. This nonstationary distribution is used to determine the complete system behavior, including the delay distributions, the blocking probability, and the density of the system size at arrival instants. Numerical examples illustrate applications of the results given.

Clare, L.

Observation of Suppressed Charged-Particle Production in Ultrarelativistic Oxygen-Oxygen Collisions

A hot and dense state of nuclear matter, known as the quark-gluon plasma, is created in collisions of ultrarelativistic heavy nuclei. Highly energetic quarks and gluons, collectively referred to as partons, lose energy as they travel through this matter, leading to suppressed production of particles with large transverse momenta (𝑝 T ). Conversely, high-𝑝 T particle suppression has not been seen in proton-lead collisions, raising questions regarding the minimum system size required to observe parton energy loss. Oxygen-oxygen (OO) collisions examine a region of effective system size that lies between these two extreme cases. The CMS detector at the CERN LHC has been used to quantify charged-particle production in inclusive OO collisions for the first time via measurements of the nuclear modification factor (𝑅 AA ). The 𝑅 AA is derived by comparing particle production to expectations based on proton-proton (𝑝⁢𝑝) data and has a value of unity in the absence of nuclear effects. The data for OO and 𝑝⁢𝑝 collisions at a nucleon-nucleon center-of-mass energy $\sqrt{s_{NN}}$ = 5.36 TeV correspond to integrated luminosities of 6.1 nb −1 and 1.02 pb −1 , respectively. The 𝑅 AA is below unity with a minimum of 0.69 ± 0.04 around 𝑝 T = 6 GeV. The data exhibit better agreement with theoretical models incorporating parton energy loss as compared to baseline models without energy loss.

FOS: Physical sciences

Absence of Barren Plateaus and Scaling of Gradients in the Energy Optimization of Isometric Tensor Network States

Abstract Vanishing gradients can pose substantial obstacles for high-dimensional optimization problems. Here we consider energy minimization problems for quantum many-body systems with extensive Hamiltonians and finite-range interactions, which can be studied on classical computers or in the form of variational quantum eigensolvers on quantum computers. Barren plateaus correspond to scenarios where the average amplitude of the energy gradient decreases exponentially with increasing system size. This occurs, for example, for quantum neural networks and for brickwall quantum circuits when the depth increases polynomially in the system size. Here we prove that the variational optimization problems for matrix product states, tree tensor networks, and the multiscale entanglement renormalization ansatz are free of barren plateaus. The derived scaling properties for the gradient variance provide an analytical guarantee for the trainability of randomly initialized tensor network states (TNS) and motivate certain initialization schemes. In a suitable representation, unitary tensors that parametrize the TNS are sampled according to the uniform Haar measure. We employ a Riemannian formulation of the gradient based optimizations which simplifies the analytical evaluation.

Barthel, Thomas

Predicting Adaptively Chosen Observables in Quantum Systems

Recent advances have demonstrated that 𝒪⁡(log 𝑀) measurements suffice to predict 𝑀 properties of arbitrarily large quantum many-body systems. However, these remarkable findings assume that the properties to be predicted are chosen independently of the data. This assumption can be violated in practice, where scientists adaptively select properties after looking at previous predictions. This work investigates the adaptive setting for three classes of observables: local, Pauli, and bounded-Frobenius-norm observables. We prove that Ω⁡(√𝑀) samples of an arbitrarily large unknown quantum state are necessary to predict expectation values of 𝑀 adaptively chosen local and Pauli observables, where the system size scales exponentially and polynomially in 𝑀, respectively. We also present computationally efficient algorithms that achieve this information-theoretic lower bound. In contrast, for bounded-Frobenius-norm observables, we devise an algorithm requiring only 𝒪⁡(log 𝑀) samples, independent of system size. These results highlight the potential pitfalls of adaptivity in analyzing data from quantum experiments and provide algorithmic tools to safeguard against erroneous predictions in quantum experiments.

Machine learning

Techno-economic assessment of residential PV system tariff policies in Jordan

This study assesses the economic and technical performance of four energy policy scenarios for Jordan's residential photovoltaic (PV) systems: net metering, net billing, zero-export with battery storage, and sell-all-buy-all. With the recent introduction of time-of-use (TOU) tariffs and policies addressing the “duck curve” effect, the research focuses on optimizing PV system sizing across different regulatory frameworks. A detailed techno-economic analysis evaluates these scenarios based on energy production, cost savings, payback periods, and energy self-sufficiency. The findings indicate that net metering and net billing offer the highest cost savings and the shortest payback periods (∼3 years). While the zero-export strategy with battery storage enhances energy self-sufficiency by up to 70%, it requires a higher upfront investment. The sell-all-buy-all scenario supports larger system sizes, achieving a low levelized cost of electricity (0.0696 USD/kWh) and a net present value of 619 USD. Additionally, the study identifies a critical feed-in tariff threshold of 0.055 USD/kWh, at which net billing becomes as financially attractive as net metering. Here, these insights offer valuable recommendations for policymakers to optimize net billing rates and TOU tariffs, promoting the expansion of Jordan's renewable energy sector.

Battery storage