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At least 1,729 records · Page 96

Best Practices for Wake Model and Optimization Algorithm Selection in Wind Farm Layout Optimization: Preprint

This paper presents the results of two case studies regarding the wind farm layout optimization problem. We asked a general audience to take part in the studies that we designed, and nine individuals participated. Case study 1 considered variations in optimization strategies for a given simple Gaussian wake model. Participants were provided with a wake model that outputs annual energy production (AEP) for an input set of wind turbine locations. Participants used an optimization method of their choosing to find an optimal wind farm layout. Case study 2 looked at trade-offs in performance resulting from variation in both physics model and optimization strategy. For case study 2, participants calculated AEP using a wake model of their choice while also implementing their chosen optimization method. Participants then used their wake model to calculate the AEP all other participant submitted turbine configurations produce for cross-comparison results. for optimized turbine locations were then cross-compared by recalculating the AEP using every other participant's wake model. Results for case study 1 show that the best optimal wind farm layouts in this study were achieved by participants who used gradient-based optimization methods. A front-runner emerged with the Sparse Nonlinear OPTimizer plus Wake Expansion Continuation (SNOPTplusWEC) optimization method, which consistently discovered a higher AEP for each scenario. Results for case study 2 show that for small wind farms with few turbines, turbine placement on the wind farm boundary is superior. Conclusions for case study 2 were drawn from participant cross-comparison of results.

17 WIND ENERGY↗

Trade-Offs of Simplified Versus Comprehensive Representation of Mineralogy When Studying Dust Impacts on Earth’s Climate Systems

The intensity and direction of dust impacts on Earth’s climate systems depend on mineral composition. For example, the presence or absence of a few percent of iron oxides in dust will determine if dust is warming or cooling the atmosphere. Similarly, feldspar will enhance ice cloud formation, while acid gases in the atmosphere will react on the surface of dust calcite limiting acid rain. Still, most climate models use a simplified representation of dust mineralogy. They assume a fixed composition at emission which stays invariant during transport and removal. Such simplification assumes spatially and temporally constant physical and chemical properties of dust, and appears to provide satisfactory results when comparing some properties with observations. The trade-off is their lack of spatial gradients, which will fail to induce circulation, cloud and precipitation changes. The two reasons to omit mineral variations are the uncertainty of current atlases of soil mineral composition in arid regions, and, more practically, an improved runtime efficiency. The former reason is losing ground with the recent launch (July 2022) of a dedicated mission (NASA/JPL EMIT) to retrieve global soil mineralogy of dust sources at high spatial resolution. While the EMIT science team is finalizing a satisfactory global map of mineral composition of dust sources, we analyzed the interaction of dust mineralogy on radiation and its impact on the fast temperature response using different representations of mineral composition from detailed and spatially varying to simplified and globally uniform, assuming different hematite contents and methods to calculate optical properties. Our results show that resolving dust mineralogy reduces dust absorption, and results in improved agreement with observation-based single scattering albedo (SSA), radiative fluxes from CERES (the Clouds and the Earth’s Radiant Energy System), and land surface temperature from CRU (Climatic Research Unit), compared to the baseline bulk dust model version. It also results in distinct radiative impacts on Earth’s climate over North Africa. From our 19-year simulation, we will show that it leads to a reduction of over 50% in net downward radiation at top of atmosphere (TOA) across the Sahara and an approximately 20% reduction over the Sahel. We will explain how the surface temperature response affects the monsoon flow from the Gulf of Guinea. Interestingly, we find similar results by simply fixing the hematite content of dust to a globally uniform value of 0.9% by volume. We will discuss the underlying reasons for such results and show that they may be unrelated to the distribution of soil mineralogy. Still, an accurate representation of soil mineralogy is necessary to better understand dust impacts on the Earth’s climate systems.

dust impacts↗

Reliability and Safety Assessment of Urban Air Mobility Concept Vehicles

The following work was commissioned by the National Aeronautics and Space Administration (NASA) to guide industry and future regulation related to urban air mobility (UAM). Prior studies compared the relative safety of NASA concept vehicles, Figure ES1, designed for UAM and provided recommendations for industry research, aircraft architectural improvements, and regulatory updates. After the prior study completed, the European Aviation Safety Agency (EASA) released regulatory guidance in the form of a special condition (SC), SC-VTOL-01, for multirotors with distributed propulsion and flight controls (DPFC). The objective of the current work was to develop DPFC architectures that will comply with SC-VTOL-01. Vehicle designs, DPFC architectures, and stability & control (S&C) models were developed to find limitations and trends to guide industry. To guide this task, NASA developed quad, hex, and an octorotor to better define vehicle attributes and trade space. Aircraft for study included electric, hybrid-electric, and turboshaft powerplants and collective and RPM control schemes. Assessments are in terms of the safety level achieved, and/or aircraft component/features needed to meet SC-VTOL-01. The most challenging criteria being the catastrophic failure rate, ≤10-9 catastrophic failures per flight hour, and that no single failures may result in a catastrophic event. A disciplined process was followed, similar to that in Aerospace Recommended Practice (ARP) 4761. A preliminary system safety assessment (PSSA) leveraged prior work as a basis of creating failure rate budgets for system design teams. System designs were updated and iterated upon, working with reliability and safety subject matter experts to develop SC-VTOL-01 compliant designs. Design changes were reflected in updated PSSAs for initial verification of compliance. The DPFC architecture was broken into four system design teams, the (1) flight control system (FCS), (2) drive and power system, (3) thermal management system (TMS), and (4) electrical power and distribution system. The FCS including elements necessary to control the aircraft, drive and power including elements necessary to generate and transmit shaft power, the TMS including elements necessary to maintain temperature limits in all operating environments, and electrical pow-er and distribution including equipment necessary to store and transmit electrical energy. Results found that all aircraft evaluated may have paths to comply with SC-VTOL-01, Figure ES2. However, S&C models showed large power transients that must be addressed and PSSA results show that future work is needed in single load path structures, high voltage power storage and distribution, and in motor/rotor overspeed protection.

Boeing↗

Evaluating Alerting and Guidance Performance of a UAS Detect-And-Avoid System

A key challenge to the routine, safe operation of unmanned aircraft systems (UAS) is the development of detect-and-avoid (DAA) systems to aid the UAS pilot in remaining "well clear" of nearby aircraft. The goal of this study is to investigate the effect of alerting criteria and pilot response delay on the safety and performance of UAS DAA systems in the context of routine civil UAS operations in the National Airspace System (NAS). A NAS-wide fast-time simulation study was conducted to assess UAS DAA system performance with a large number of encounters and a broad set of DAA alerting and guidance system parameters. Three attributes of the DAA system were controlled as independent variables in the study to conduct trade-off analyses: UAS trajectory prediction method (dead-reckoning vs. intent-based), alerting time threshold (related to predicted time to LoWC), and alerting distance threshold (related to predicted Horizontal Miss Distance, or HMD). A set of metrics, such as the percentage of true positive, false positive, and missed alerts, based on signal detection theory and analysis methods utilizing the Receiver Operating Characteristic (ROC) curves were proposed to evaluate the safety and performance of DAA alerting and guidance systems and aid development of DAA system performance standards. The effect of pilot response delay on the performance of DAA systems was evaluated using a DAA alerting and guidance model and a pilot model developed to support this study. A total of 18 fast-time simulations were conducted with nine different DAA alerting threshold settings and two different trajectory prediction methods, using recorded radar traffic from current Visual Flight Rules (VFR) operations, and supplemented with DAA-equipped UAS traffic based on mission profiles modeling future UAS operations. Results indicate DAA alerting distance threshold has a greater effect on DAA system performance than DAA alerting time threshold or ownship trajectory prediction method. Further analysis on the alert lead time (time in advance of predicted loss of well clear at which a DAA alert is first issued) indicated a strong positive correlation between alert lead time and DAA system performance (i.e. the ability of the UAS pilot to maneuver the unmanned aircraft to remain well clear). While bigger distance thresholds had beneficial effects on alert lead time and missed alert rate, it also generated a higher rate of false alerts. In the design and development of DAA alerting and guidance systems, therefore, the positive and negative effects of false alerts and missed alerts should be carefully considered to achieve acceptable alerting system performance by balancing false and missed alerts. The results and methodology presented in this study are expected to help stakeholders, policymakers and standards committees define the appropriate setting of DAA system parameter thresholds for UAS that ensure safety while minimizing operational impacts to the NAS and equipage requirements for its users before DAA operational performance standards can be finalized.

UAS Detect-and-Avoid (DAA) System↗

Radiobiological Determination of Dose Escalation and Normal Tissue Toxicity in Definitive Chemoradiation Therapy for Esophageal Cancer

Purpose: This study investigated the trade-off in tumor coverage and organ-at-risk sparing when applying dose escalation for concurrent chemoradiation therapy (CRT) of mid-esophageal cancer, using radiobiological modeling to estimate local control and normal tissue toxicity. Methods and Materials: Twenty-one patients with mid-esophageal cancer were selected from the SCOPE1 database (International Standard Randomised Controlled Trials number 47718479), with a mean planning target volume (PTV) of 327 cm{sup 3}. A boost volume, PTV2 (GTV + 0.5 cm margin), was created. Radiobiological modeling of tumor control probability (TCP) estimated the dose required for a clinically significant (+20%) increase in local control as 62.5 Gy/25 fractions. A RapidArc (RA) plan with a simultaneously integrated boost (SIB) to PTV2 (RA{sub 62.5}) was compared to a standard dose plan of 50 Gy/25 fractions (RA{sub 50}). Dose-volume metrics and estimates of normal tissue complication probability (NTCP) for heart and lungs were compared. Results: Clinically acceptable dose escalation was feasible for 16 of 21 patients, with significant gains (>18%) in tumor control from 38.2% (RA{sub 50}) to 56.3% (RA{sub 62.5}), and only a small increase in predicted toxicity: median heart NTCP 4.4% (RA{sub 50}) versus 5.6% (RA{sub 62.5}) P<.001 and median lung NTCP 6.5% (RA{sub 50}) versus 7.5% (RA{sub 62.5}) P<.001. Conclusions: Dose escalation to the GTV to improve local control is possible when overlap between PTV and organ-at-risk (<8% heart volume and <2.5% lung volume overlap for this study) generates only negligible increase in lung or heart toxicity. These predictions from radiobiological modeling should be tested in future clinical trials.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Optimization under uncertainty of a hybrid waste tire and natural gas feedstock flexible polygeneration system using a decomposition algorithm

Market uncertainties motivate the development of flexible polygeneration systems that are able to adjust operating conditions to favor production of the most profitable product portfolio. However, this operational flexibility comes at the cost of higher capital expenditure. A scenario-based two-stage stochastic nonconvex Mixed-Integer Nonlinear Programming (MINLP) approach lends itself naturally to optimizing these trade-offs. This work studies the optimal design and operation under uncertainty of a hybrid feedstock flexible polygeneration system producing electricity, methanol, dimethyl ether, olefins or liquefied (synthetic) natural gas. A recently developed C++ based software framework (named GOSSIP) is used for modeling the optimization problem as well as its efficient solution using the Nonconvex Generalized Benders Decomposition (NGBD) algorithm. Two different cases are studied: The first uses estimates of the means and variances of the uncertain parameters from historical data, whereas the second assesses the impact of increased uncertain parameter volatility. The value of implementing flexible designs characterized by the value of the stochastic solution (VSS) is in the range of 260–405 M$ for a scale of approximately 893 MW of thermal input. Increased price volatility around the same mean results in higher expected net present value and VSS as operational flexibility allows for asymmetric exploitation of price peaks.

42 ENGINEERING↗

Computational design and engineering of an Escherichia coli strain producing the nonstandard amino acid para -aminophenylalanine

Introducing heterologous pathways into host cells constitutes a promising strategy for synthesizing nonstandard amino acids (nsAAs) to enable the production of proteins with expanded chemistries. However, this strategy has proven challenging, as the expression of heterologous pathways can disrupt cellular homeostasis of the host cell. Here, we sought to optimize the heterologous production of the nsAA para -aminophenylalanine (pAF) in Escherichia coli . First, we incorporated a heterologous pAF biosynthesis pathway into a genome-scale model of E. coli metabolism and computationally identified metabolic interventions in the host’s native metabolism to improve pAF production. Next, we explored different approaches of imposing these flux interventions experimentally and found that the upregulation of flux in the chorismate biosynthesis pathway through the elimination of feedback inhibition mechanisms could significantly raise pAF titers (~20-fold) while maintaining a reasonable pAF production-growth rate trade-off. Overall, this study provides a promising strategy for the biosynthesis of nsAAs in engineered cells.

59 BASIC BIOLOGICAL SCIENCES↗

Benchmarking optimization methods for materials research: Gradient descent and Bayesian optimization for lithium-ion battery aging diagnostics

Accurate and efficient parameter estimation is essential for battery diagnostics and aging analysis. Here, in this study, we compare two optimization-based approaches—gradient descent and Bayesian optimization—for extracting parameters from differential voltage analysis in lithium-ion batteries. While these techniques are widely used, their relative strengths and limitations for this application are not well understood. The study evaluates the trade-offs between these methods in terms of result quality, computational cost, and reliability within this specific application. The diagnostic results from our battery data suggest adopting gradient descent as an initial method for rapid and efficient analysis, while employing more stable optimization techniques, such as Bayesian optimization, as a verification step to mitigate potential instability. Comparing the two methods provides information on algorithmic choice, while inspiring further discussions on selecting appropriate techniques for specific research tasks.

Zhao, Ziqing [Boston Univ., MA (United States)] (O↗

Technical Performance and Economic Evaluation of Evaporative and Membrane-Based Concentration for Biomass-Derived Sugars

Several conversion pathways of lignocellulosic biomass to advanced biofuels require or benefit from using concentrated sugar syrups of 600 g/L or greater. And while concentration may seem straightforward, thermal sugar degradation and energy efficiency remain major concerns. This study evaluated the trade-offs in product recovery, energy consumption, and economics between evaporative and membrane-based concentration methods. The degradation kinetics of xylose and glucose were characterized and applied to an evaporator process simulation. Though significant sugar loss was predicted for certain scenarios due to the Maillard reaction, industrially common falling-film plate evaporators offer short residence times (<5 min) and are expected to limit sugar losses. Membrane concentration experiments characterized flux and sugar rejection, but diminished flux occurred at >100 g/L. A second step using evaporation is necessary to achieve target concentrations. Techno-economic process model simulations evaluated the overall economics of concentrating a 35 g/L sugar stream to 600 g/L in a full-scale biorefinery. A two-step approach of preconcentrating using membranes and finishing with an evaporator consumed less energy than evaporation alone but was more expensive because of high capital expenses of the membrane units.

09 BIOMASS FUELS↗

Oxide-Encapsulated Ruthenium Oxide Catalysts for Selective Oxygen Evolution in Unbuffered pH-Neutral Seawater

Direct seawater electrolysis is a promising approach to producing green hydrogen in water-scarce environments using renewable energy. However, the undesirable chlorine evolution reaction and hypochlorite evolution reaction compete with the desired oxygen evolution reaction (OER) at the anode electrocatalyst. This issue is most pronounced in unbuffered pH-neutral solutions due to local acidification resulting from the OER. To overcome this challenge, this study provides a comprehensive evaluation of the use of silicon oxide (SiO x ) and titanium oxide (TiO x ) nanoscale overlayers coated on metallic ruthenium (Ru) and ruthenium oxide (RuO x ) thin film electrodes and their ability to block chloride ions from reaching active sites during operation in an unbuffered 0.6 M NaCl electrolyte. Using a combination of (electro)analytical techniques, encapsulated RuO x anodes are shown to effectively suppress Cl - transport to buried catalyst active sites while allowing for the desired OER to occur, leading to increases in OER faradaic efficiency at moderate overpotentials. Evidence for the ability of SiO x overlayers to block Cl - ions from reaching the active buried interface was obtained by monitoring the ν(O-H) stretching mode of OH adsorbates using in situ Raman spectroscopy. Here, this study also reports trade-offs between the activity, selectivity, and stability of bare and encapsulated Ru and RuO x electrocatalysts, finding that the magnitude of these trade-offs strongly depends on the complex interplay between electrode architecture, material properties, and catalytic performance, especially in unbuffered pH-neutral seawater.

58 GEOSCIENCES↗

High Li + Transference Number Electrolyte Enabled by Fluoride Acceptor for Low-Temperature Li-Ion Batteries

To enable wide-temperature operation of lithium-ion batteries (LIBs), new electrolyte formulations have been developed to enhance the performance, particularly at low temperatures. A key challenge lies in achieving both high ionic conductivity and a high lithium-ion transference number due to their inherent trade-off. In this study, we designed an electrolyte system comprising tris(pentafluorophenyl)borane (TPFPB), a fluoride acceptor, and LiF salt in ethylene carbonate (EC)-free solvents. TPFPB, with its electron-deficient boron center, facilitates fluoride transfer reactions that promote the dissociation of otherwise insoluble LiF. When methyl acetate (MA) was used as the solvent, the electrolyte exhibited a high transference number (t Li + = 0.85) and ionic conductivity (σ = 5.0 × 10 –3 S cm –1 ). The optimized electrolyte demonstrated excellent performance at −20 °C, with no evidence of lithium plating. This work presents a new strategy for electrolyte design by leveraging cation desolvation to achieve high-performance LIBs for low-temperature and high-power applications.

anions↗

A Comparative Study of Physics‐Informed and Data‐Driven Neural Networks for Compound Flood Simulation at River‐Ocean Interfaces: A Case Study of Hurricane Irene

Simulating compound flooding (CF) at the river-ocean interface within large-scale Earth System Models (ESMs) presents significant challenges due to complex interactions between river discharge, storm surge, and tides. This study assesses the comparative advantages of physics-informed and data-driven machine learning (ML) approaches for enhancing local ESM performance. We systematically compare data-driven neural network models (i.e., CNNs, U-Net, Long Short-Term Memory (LSTM), Gated Recurrent Unit), and physics-informed neural network (PINN) models, including vanilla PINN and a finite-difference-based PINN (FD-PINN). Specifically, FD-PINN is introduced to enhance computational efficiency, accelerating vanilla PINNs by ∼6.5 times while improving accuracy. To enhance data-driven model training, a new data-generation approach is developed to sample historical fluvial and coastal flood events, which ensures a robust data set for extreme event prediction. The models are evaluated using a realistic one-dimensional river domain extracted from an ESM's river mesh and the Hurricane Irene event as an independent test case. Results show that FD-PINN achieves accurate predictions with significantly reduced computational costs relative to vanilla PINNs. Among data-driven models, the best overall performance is achieved by a CNN-LSTM hybrid, which balances accuracy and efficiency. While a fully connected CNN (CNN-FC) provides the best accuracy, it incurs high computational cost. Architectures lacking strong temporal modeling tend to underperform on unseen events. These findings highlight the importance of sequence-aware designs for robust generalization. This study reveals the trade-offs between physics-informed and data-driven models and proposes an adaptive hybrid framework for integrating ML into ESMs to enhance local flood simulations.

Earth Systems Modeling↗

Non-averaged single-molecule tertiary structures reveal RNA self-folding through individual-particle cryo-electron tomography

Large-scale and continuous conformational changes in the RNA self-folding process present significant challenges for structural studies, often requiring trade-offs between resolution and observational scope. Here, we utilize individual-particle cryo-electron tomography (IPET) to examine the post-transcriptional self-folding process of designed RNA origami 6-helix bundle with a clasp helix (6HBC). By avoiding selection, classification, averaging, or chemical fixation and optimizing cryo-ET data acquisition parameters, we reconstruct 120 three-dimensional (3D) density maps from 120 individual particles at an electron dose of no more than 168 e - Å -2 , achieving averaged resolutions ranging from 23 to 35 Å, as estimated by Fourier shell correlation (FSC) at 0.5. Each map allows us to identify distinct RNA helices and determine a unique tertiary structure. Statistical analysis of these 120 structures confirms two reported conformations and reveals a range of kinetically trapped, intermediate, and highly compacted states, demonstrating a maturation folding landscape likely driven by helix-helix compaction interactions.

36 MATERIALS SCIENCE↗

Analysis of Power-Maximizing Region 2 Controllers for Wind and Marine Turbines

Wind and marine energy are rapidly growing and complementary technologies that share some techniques for simplified modeling and control, particularly in below-rated flow speeds. A turbine operator has several choices of controller for maximizing power in Region 2. The simple and ubiquitous KΩ 2 control law is often effective but limited in its flexibility. Alternative controllers use reference tracking to split the control objectives into a low-bandwidth optimal tip-speed ratio tracking loop to maximize steady-state power and a higher-bandwidth proportional-integral control loop to reject inflow turbulence. Several options exist for identifying the slowly varying optimal set point during operation, based on estimating the inflow velocity or filtering the power or torque signals. This study compares the trade-offs between performance and other design priorities for a few choices of reference-tracking controller in the literature for reference wind and marine turbines. Analysis is performed in the frequency domain using the linearization of each controller, and the impact of turbulent disturbances on the closed-loop system is described. The controllers are simulated in OpenFAST to analyze their performance with higher-order nonlinear turbine dynamics.

17 WIND ENERGY↗

Dynamical structure factors of warm dense matter from time-dependent orbital-free and mixed-stochastic-deterministic density functional theory

Abstract We present the first calculations of the inelastic part of the dynamical structure factor (DSF) for warm dense matter (WDM) using time-dependent orbital-free density functional theory (TD-OF-DFT) and mixed-stochastic-deterministic (mixed) Kohn Sham TD-DFT (KS TD-DFT). WDM is an intermediate phase of matter found in planetary cores and laser-driven experiments, where the accurate calculation of the DSF is critical for interpreting x-ray Thomson scattering measurements. Traditional TD-DFT methods, while highly accurate, are computationally expensive, motivating the exploration of TD-OF-DFT and mixed TD-KS-DFT as more efficient alternatives. We applied these methods to experimentally measured WDM systems, including solid-density aluminum and beryllium, compressed beryllium, and carbon–hydrogen mixtures. Our results show that TD-OF-DFT requires a dynamical kinetic energy potential in order to qualitatively capture the plasmon response. Additionally, it struggles with capturing bound electron contributions. In contrast, mixed TD-KS-DFT offers greater accuracy in distinguishing bound and free electron effects, aligning well with experimental data, though at a higher computational cost. This study highlights the trade-offs between computational efficiency and accuracy, demonstrating that TD-OF-DFT remains a valuable tool for rapid scans of parameter space, while mixed TD-KS-DFT should be preferred for high-fidelity simulations. Our findings provide insight into the future development of DFT methods for WDM and suggest potential improvements for TD-OF-DFT.

36 MATERIALS SCIENCE↗

Time-Energy Uncertainty Relation for Noisy Quantum Metrology

Detection of very weak forces and precise measurement of time are two of the many applications of quantum metrology to science and technology. To sense an unknown physical parameter, one prepares an initial state of a probe system, allows the probe to evolve as governed by a Hamiltonian 𝐻 for some time 𝑡, and then measures the probe. If 𝐻 is known, we can estimate 𝑡 by this method; if 𝑡 is known, we can estimate classical parameters on which 𝐻 depends. The accuracy of a quantum sensor can be limited by either intrinsic quantum noise or by noise arising from the interactions of the probe with its environment. In this work, we introduce and study a fundamental trade-off, which relates the amount by which noise reduces the accuracy of a quantum clock to the amount of information about the energy of the clock that leaks to the environment. Specifically, we consider an idealized scenario in which a party Alice prepares an initial pure state of the clock, allows the clock to evolve for a time that is not precisely known, and then transmits the clock through a noisy channel to a party Bob. Meanwhile, the environment (Eve) receives any information about the clock that is lost during transmission. We prove that Bob’s loss of quantum Fisher information about the elapsed time is equal to Eve’s gain of quantum Fisher information about a complementary energy parameter. We also prove a similar, but more general, trade-off that applies when Bob and Eve wish to estimate the values of parameters associated with two noncommuting observables. We derive the necessary and sufficient conditions for the accuracy of the clock to be unaffected by the noise, which form a subset of the Knill-Laflamme error-correction conditions. A state and its local time-evolution direction, if they satisfy these conditions, are said to form a metrological code. We provide a scheme to construct metrological codes in the stabilizer formalism. We show that there are metrological codes that cannot be written as a quantum error-correcting code with similar distance in which the Hamiltonian acts as a logical operator, potentially offering new schemes for constructing states that do not lose any sensitivity upon application of a noisy channel. We discuss applications of the trade-off relation to sensing using a quantum many-body probe subject to erasure or amplitude-damping noise.

metrology↗

Evaluating HPC Scheduling Strategies for Urgent Workloads

Scientific computing centers increasingly face workloads with diverse urgency requirements, driven by applications that demand rapid or even immediate execution. Appropriately configured scheduling policies can significantly improve both user satisfaction and overall cluster utilization. In this work, we present a systematic analysis of scheduler configurations under scenarios where a fraction of jobs have urgent computing needs. We evaluate multiple job scheduling simulators, develop a lightweight job-submission emulation framework, and create tools to analyze and visualize the resulting scheduling data. Our study identifies key trade-offs between responsiveness, fairness, and efficiency, and offers a set of practical scheduling configurations (particularly for Slurm) that can be tailored to HPC environments supporting mixed-urgency workloads.

Maheshwari, Ketan [ORNL] (ORCID:000000033800662X)↗

Theoretical and Computational Modeling of a Plasma Wakefield BBU Instability

Plasma wakefield accelerators achieve accelerating gradients on the order of the wave-breaking limit, m c² k_{p}/e, so that higher accelerating gradients correspond to shorter plasma wavelengths. Small-scale accelerating structures, such as plasma and dielectric wakefields, are susceptible to the beam break-up instability (BBU), which can be understood from the Panofsky-Wenzel theorem: if the fundamental accelerating mode scales as b⁻¹ for a structure radius b, then the dipole mode must scale as b⁻³, meaning that high accelerating gradients necessarily come with strong dipole wake fields. Because of this relationship, any plasma-accelerator-based future collider will require detailed study of the trade-offs between extracting the maximum energy from the driver and mitigating the beam break-up instability. Recent theoretical work* predicts the tradeoff between the witness bunch stability and the amount of energy that can be extracted from the drive bunch, a so-called efficiency-instability relation . We will discuss the beam break-up instability and the efficiency-instability relation and the theoretical assumptions made in reaching this conclusion. We will also present preliminary particle-in-cell simulations of a beam-driven plasma wakefield accelerator used to test the domain of validity for the assumptions made in this model.

43 PARTICLE ACCELERATORS↗