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At least 523 records · Page 29

HP-FLEX: Field Demonstration of the Semantics-Driven Configuration of a Model Predictive Control System to Make Heat Pumps Flexible

Model Predictive Control (MPC) has demonstrated significant potential for optimizing building operations and enabling demand flexibility. However, the widespread adoption of MPC is hindered by complex manual configuration and commissioning processes that must be conducted by control experts working alongside building operators. These challenges drive up costs and reduce scalability, particularly when technical human resources and building automation systems are limited, such as in small and medium commercial buildings (SMCBs). This paper demonstrates how semantic standards, specifically ASHRAE 223P, can accelerate the adoption of MPC applications for load flexibility in SMCBs. The authors present a replicable control framework, titled “HP-FLEX” that leverages a building’s semantic model to bootstrap the required data configuration for an MPC controller developed for optimizing heat pump systems as flexible grid resources. The semantic model helps streamline the deployment workflow, particularly for site setup, data/control commissioning, and model setup. This integration enhances portability, transferability, and scalability of the HP-FLEX MPC, which has been developed to support MPC-based supervisory HVAC controllers in SMCBs. Additionally, the paper details the required building and thermostat metadata information to enable the HP-FLEX MPC based on field demonstrations. The new workflow was tested in a small commercial building located in California, U.S., and demonstrated a load shifting performance of 9% based on a dynamic pricing signal that varies by the hour. This work provides a practical pathway for transitioning sophisticated building applications from custom to standardized semantic representations, supporting the broader adoption of advanced control strategies like MPC. The framework also establishes a foundation for evolving metadata requirements as applications mature while maintaining compatibility with industry standards.

Paul, Lazlo↗

The steady growth of the high-energy spectral cut-off in relativistic magnetic reconnection

Magnetic reconnection is invoked as an efficient particle accelerator in a variety of astrophysical sources of non-thermal high-energy radiation. With large-scale two-dimensional particle-in-cell simulations of relativistic reconnection (i.e. with magnetization σ >> 1) in pair plasmas, we study the long-term evolution of the power-law slope and high-energy cut-off of the spectrum of accelerated particles. We find that the high-energy spectral cut-off does not saturate at γcut ~ 4σ, as claimed by earlier studies, but it steadily grows with time as long as the reconnection process stays active. At late times, the cut-off scales approximately as γ cut ∝√t, regardless of the flow magnetization and initial temperature. We show that the particles dominating the high-energy spectral cut-off reside in plasmoids, and in particular in a strongly magnetized ring around the plasmoid core. The growth of their energy is driven by the increase in the local field strength, coupled with the conservation of the first adiabatic invariant. We also find that the power-law slope of the spectrum (p = -d log N/d log γ) evolves with time. For σ ≳ 10, the spectrum is hard at early times (p ≲ 2), but it tends to asymptote to p ~ 2; the steepening of the power-law slope allows the spectral cut-off to extend to higher and higher energies, without violating the fixed energy budget of the system. Our results demonstrate that relativistic reconnection is a viable candidate for accelerating the high-energy particles emitting in relativistic astrophysical sources.

79 ASTRONOMY AND ASTROPHYSICS↗

Development of a rapid-transit system for precision nuclear physics measurements

A Rapid Belt-driven Irradiated Target Transfer System, named RABITTS, was developed for use at the Triangle Universities Nuclear Laboratory. This system allows for cyclic activation with neutron or photon beams, and measurement of reaction products using γ-ray spectroscopy. Both a 1 meter and 10 meter transfer system have been developed with transit times as low as 0.4 and 1.0 seconds, respectively. The systems are deployed at the tandem accelerator laboratory for use with monoenergetic neutron beams, and at the High-Intensity γ-ray Source facility for activation using photon beams. A detailed characterization of the systems’ performance and sensitivity is presented. In order to produce the highest accuracy cross-section data, a model for calculating corrections to cyclic activation with variable beam flux is developed and presented. We have commissioned these systems by measuring 197m Au, where we report a measured half-life of 7.73 ± 0.05 s and a 197 Au(n, n') 197m Au isomer production cross of 628 ± 28 mb at neutron energy E n = 2.0 MeV. In addition, we measured 90m Zr, where we report a measured half-life of 799.7 ± 8.0 ms and a 90 Zr(n, n') 90m Zr isomer production cross of 180 ± 12 mb at E n = 4.6 MeV. Furthermore, these measured half-lives are in excellent agreement with the evaluated values and the cross-section measurements are performed at previously unmeasured incident neutron energies.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Artificial intelligence time series forecasting for feed-forward laser stabilization

Laser plasma accelerators, typically operating at 1–10 Hz repetition rates, have the ability to produce high-quality electron beams in compact, all-optical-driven configurations, with the electron beams uniquely suited for a wide variety of accelerator-based applications. However, fluctuations and drifts in the laser delivery to the meter-scaled and below plasma target (the electron beam source) will translate into electron beam source variations that can limit their utility for demanding applications like light sources or linear colliders. Commercially available active feedback laser stabilization systems are intrinsically bandwidth limited due to their integration with multi-inch corrective mirror mounts which minimizes their effectiveness. In this manuscript, we present a Neural Network time series forecaster that can predict laser position fluctuations of the laser delivery to the final target well ahead of a future laser shot. The Root-Mean-Square-Error (RMSE) of the prediction accuracy was < 2 μ m for a 1 / e 2 beam radius of 34 μ m . Our feed-forward approach serves as a first-step in circumventing the bandwidth limitations imposed by the currently available stabilization systems since it allows for mirrors to be moved into position ahead of time to offset the predicted future position drift. This will help advance laser plasma accelerator research by providing greater robustness and stability needed for its applications.

Berger, Curtis↗

From lab to lamp: Understanding downconverter degradation in LED packages

Downconverters, primarily inorganic phosphors, are critical components in white solid-state LED-based lighting and liquid crystal display backlights. Research efforts have led to a fundamental understanding of a downconverter's absorption, photoluminescence, and efficiency as a function of composition, structure, and processing conditions. However, considerably less work has focused on the reliability of phosphors once they are incorporated into LED packages. Solving these issues is often the final step before the commercialization of new materials, but the significant resources and time required to evaluate and mitigate materials failure are rarely discussed in the literature. In this Perspective, we discuss the need for conducting downconverter reliability testing and the potential of accelerating, screening, and understanding downconverter failure modes. Our focus highlights the mechanisms of failure and discusses how this influences materials selection and the design of different LED packages. We also stress the potential for accelerated reliability testing protocols and note the potential role first-principles calculations and data-driven models could play in establishing the compositional-processing trends for different aspects of downconverter reliability. In conclusion, we close with possible research directions that could improve downconverter reliability and emphasize the importance of assessing a material's (chemical) stability where multiple manufacturing and processing steps can dictate system performance.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Microgravity and its effects on residual motions in fluids

The primary reason for conducting many materials science experiments in space is to minimize or eliminate undesirable effects that might result owing to convective motions in fluids that are driven by buoyancy effects. Of particular concern are the low frequency accelerations caused by the Earth's gravity gradient field, spacecraft attitude motions, and atmospheric drag. In order to gain a limited understanding of the effects of these accelerations, researchers calculated the Stokes' motion of a spherical particle in a fluid for various types of spacecraft attitudes. Researchers assessed the effect of slowly rotating the experimental system relative to the spacecraft in order to reduce the rate at which the particles accumulate against the container wall.

Alexander, J. Iwan D.↗

Buoyancy-Driven Instabilities in Single-Bubble Sonoluminescence

The principal objectives of this study are to determine how gravity affects the emission of light from single-bubble sonoluminescence (SBSL), and whether or not the bubble extinction is directly related to gravity. Our experimental task involves designing glass or quartz spherical levitation cells that generate very stable SL bubbles. The cells must have minimized vibration, and some temperature control. The experimental system will reside in a light-tight enclosure. Aside from acceleration, the frequency, pressure amplitude, and light intensity must be measured. A computer program will be constructed to perform all aspects of the experiment.

Matula, Thomas J.↗

NASA Tech Briefs, January 2004

Topics covered include: Multisensor Instrument for Real-Time Biological Monitoring; Sensor for Monitoring Nanodevice-Fabrication Plasmas; Backed Bending Actuator; Compact Optoelectronic Compass; Micro Sun Sensor for Spacecraft; Passive IFF: Autonomous Nonintrusive Rapid Identification of Friendly Assets; Finned-Ladder Slow-Wave Circuit for a TWT; Directional Radio-Frequency Identification Tag Reader; Integrated Solar-Energy-Harvesting and -Storage Device; Event-Driven Random-Access-Windowing CCD Imaging System; Stroboscope Controller for Imaging Helicopter Rotors; Software for Checking State-charts; Program Predicts Broadband Noise from a Turbofan Engine; Protocol for a Delay-Tolerant Data-Communication Network; Software Implements a Space-Mission File-Transfer Protocol; Making Carbon-Nanotube Arrays Using Block Copolymers: Part 2; Modular Rake of Pitot Probes; Preloading To Accelerate Slow-Crack-Growth Testing; Miniature Blimps for Surveillance and Collection of Samples; Hybrid Automotive Engine Using Ethanol-Burning Miller Cycle; Fabricating Blazed Diffraction Gratings by X-Ray Lithography; Freeze-Tolerant Condensers; The StarLight Space Interferometer; Champagne Heat Pump; Controllable Sonar Lenses and Prisms Based on ERFs; Measuring Gravitation Using Polarization Spectroscopy; Serial-Turbo-Trellis-Coded Modulation with Rate-1 Inner Code; Enhanced Software for Scheduling Space-Shuttle Processing; Bayesian-Augmented Identification of Stars in a Narrow View; Spacecraft Orbits for Earth/Mars-Lander Radio Relay; and Self-Inflatable/Self-Rigidizable Reflectarray Antenna.

Source record↗

Microbial Vessel for Impedance Spectroscopy and Electrochemistry (Mvise): an Extensible, Interoperable Data Acquisition Platform for Liquid Culture Studies in Space Biology Research

The White House Office of Science and Technology Policy (OSTP) has declared 2023 to be the Year of Open Science following an initiative to democratize scientific knowledge. Simultaneously, new sensor technologies have broadened the experimental space available to bioastronautics research. With these open-science goals and technological advances in mind, we have designed and constructed a data acquisition platform for high-precision, real-time monitoring of liquid culture systems. The vessel rig is fitted with six Atlas Scientific probes (micro pH, electrical conductivity, dissolved oxygen, oxidation-reduction potential, liquid temperature, air CO2) and a custom optical density probe similar to the one on BioSentinel’s BioSensor payload. A custom dielectric spectroscopy probe is also planned. The structure of the vessel is resin 3-D printed on a hobbyist-level machine, reducing the production cost and iteration time by over 60% each while increasing extensibility. Data acquisition and storage is controlled with a standalone C state machine-based program running on a Raspberry Pi 3 Model B. When not running headless, an additional program automatically generates and updates plots for live data visualization. Validation of the rig as a data collection system was performed with a yeast liquid culture experiment. While the vessel rig is currently used for standalone experiments, it can also be used as the base perception unit in a self-driving laboratory (SDL). SDLs are high-throughput data collection systems that employ automation and artificial intelligence to conduct and manage routine experiments. Here, we envision an SDL driven by several vessel rigs in which an automated script compares key results, informing the design of future experiments. A vessel rig SDL would streamline many operations, including 1) strain selection for the Lunar Explorer Instrument for space biology Applications (LEIA) investigation and 2) the study of bioregenerative life support systems (BLSS). Ultimately, the datasets that can now be acquired will provide crucial information for accelerating bioastronautics application development in the era of commercial space.

Stephen Lantin↗

An Overview of Experiments and Modeling of Polysiloxane-Coated Thermal Protection Systems for Missions to Mars, Titan, and Beyond.

Phenolic Impregnated Carbon Ablator (PICA) gained heritage during the historic Stardust mission, where it successfully returned samples from a comet’s tail and has since been instrumental in delivering payloads to the surface of Mars [1-3]. Most recently, PICA enabled the safe return of samples collected from asteroid Bennu as part of the OSIRIS-REx mission. This rich legacy underscores PICA’s critical role in allowing NASA’s most ambitious exploration missions. However, the friable nature of its phenolic phase presents challenges during handling and pre-launch activities. To mitigate this issue, PICA is coated with a polysiloxane resin system, which serves to suppress particulate dispersion and thereby safeguard spacecraft components. A comprehensive understanding of the polysiloxane resin’s behavior is imperative, as it profoundly shapes the material response of PICA during atmospheric entry by influencing its thermal and oxidative stability. This influence extends to thermocouple plugs embedded within thermal protection systems. These plugs have demonstrated their significance in missions such as Mars Science Laboratory (MSL) and Mars 2020, where the MEDLI and MEDLI2 instrumentation suites delivered in-valuable insights into the performance of thermal protection systems during entry into the Martian atmosphere [4]. Looking ahead, missions such as Dragonfly, set to descend into Titan’s dense atmosphere, aim to leverage advanced sensor technologies to further refine our understanding of thermal protection response [5]. Moreover, thermocouple plugs play an essential role in validating cutting-edge material response models, such as those pioneered under NASA’s Entry Systems Modeling Project (ESM), designed, in-part, to predict the operational integrity of thermal protection systems under the extreme stresses of atmospheric entry. To achieve these modeling goals, ground-based experiments are crucial to provide the foundational data necessary for developing and refining these predictive tools. To this end, an extensive test campaign was conducted at the Hypersonic Materials Environmental Test System (HyMETS) to investigate the high-temperature behavior of the polysiloxane resin in an air environment [6]. These experiments revealed critical phenomena, including the formation of a silicon oxycarbide layer that enhances oxidation resistance, moderates surface temperatures, and alters in-depth thermal response. Building on these findings, subsequent tests were designed to simulate atmospheric entry conditions in reactive gases, such as CO2 and N2, to mimic the environments of Mars and Titan, respectively, as well as non-reactive gases representing the atmospheres of the Ice Giants (Neptune and Uranus). A heating rate dependent decomposition mechanism has been identified for the polysiloxane resin under oxidizing conditions (Fig. 1). In the initial stage, the resin and the underlying thermal protection system undergo pyrolysis, rapidly generating a thin amorphous silicon oxycarbide interwoven with carbonaceous char and residual fibers from PICA. During the second stage, the nascent oxide layer establishes a robust, oxidation-resistant thermal barrier coating, which significantly impedes heat transfer to the underlying carbonaceous char, resulting in a stagnation of the surface temperature. A key factor contributing to this thermal resistance is the low recombination efficiency of atomic oxygen (γ), which further diminishes the heat load on the material’s interior layers [7]. Moreover, as the surface temperature stagnates, the silicon oxycarbide phase separates into distinct regions of silica and free graphite. Ultimately, when the heat flux reaches a critical threshold, a third stage is triggered, leading to the breakdown of the coating through carbothermal reduction, exposing the underlying char layer. This exposure leads to a dramatic surface temperature spike, driven by highly exothermic reactions between atomic oxygen and the char layer, further accelerating material degradation. A detailed mass and heat transfer model of PICA coated with polysiloxane resin was implemented in the Porous material Analysis Toolbox based on OpenFOAM, PATO [8]. The initial stage was considered negligible in this model because the resin decomposition occurs rapidly within a thin surface layer. Instead, the coating was directly considered as an oxygen-resistant thermal barrier coating. For the second stage, the thin amorphous silicon oxycarbide was treated as a pure silica surface to simplify the thermochemical behavior. The model ac-counts for surface equilibrium processes using representative elements of the coating-environment system. For the third stage, specific boundary conditions were developed to estimate the onset and progression of the coating removal. Two-dimensional material response simulations were conducted to compare uncoated and coated PICA using boundary conditions calibrated with HyMETS data. Fig. 2 illustrates that the simulations closely align with experimental data, successfully reproducing measured temperature profiles. This work will include the latest advancements in the coating model, including the calibration of recombination of atomic oxygen at the surface during the second phase. These simulated results will be further validated against additional CO2 data points from HyMETS, reinforcing the models’ predictive capabilities. These mechanisms and their effects on thermal protection systems, including thermochemical behavior and thermocouple probe performance in extreme environments, provide crucial insights for optimizing spacecraft designs that safeguard scientific payload and ensure mission success in future planetary exploration endeavors.

Active Oxidation↗

WE-G-BRA-02: SafetyNet: Automating Radiotherapy QA with An Event Driven Framework

Purpose: Quality assurance is an essential task in radiotherapy that often requires many manual tasks. We investigate the use of an event driven framework in conjunction with software agents to automate QA and eliminate wait times. Methods: An in house developed subscription-publication service, EventNet, was added to the Aria OIS to be a message broker for critical events occurring in the OIS and software agents. Software agents operate without user intervention and perform critical QA steps. The results of the QA are documented and the resulting event is generated and passed back to EventNet. Users can subscribe to those events and receive messages based on custom filters designed to send passing or failing results to physicists or dosimetrists. Agents were developed to expedite the following QA tasks: Plan Revision, Plan 2nd Check, SRS Winston-Lutz isocenter, Treatment History Audit, Treatment Machine Configuration. Results: Plan approval in the Aria OIS was used as the event trigger for plan revision QA and Plan 2nd check agents. The agents pulled the plan data, executed the prescribed QA, stored the results and updated EventNet for publication. The Winston Lutz agent reduced QA time from 20 minutes to 4 minutes and provided a more accurate quantitative estimate of radiation isocenter. The Treatment Machine Configuration agent automatically reports any changes to the Treatment machine or HDR unit configuration. The agents are reliable, act immediately, and execute each task identically every time. Conclusion: An event driven framework has inverted the data chase in our radiotherapy QA process. Rather than have dosimetrists and physicists push data to QA software and pull results back into the OIS, the software agents perform these steps immediately upon receiving the sentinel events from EventNet. Mr Keranen is an employee of Varian Medical Systems. Dr. Moran’s institution receives research support for her effort for a linear accelerator QA project from Varian Medical Systems. Other quality projects involving her effort are funded by Blue Cross Blue Shield of Michigan, Breast Cancer Research Foundation, and the NIH.

60 APPLIED LIFE SCIENCES↗

Particle Beam Acceleration Using 3 Petawatt Laser Pulses

The Zettawatt-Equivalent Ultrashort pulse laser System (ZEUS) is presently operational at the Gerard Mourou Center for Ultrafast Optical Science (CUOS) at the University of Michigan. ZEUS is a significant upgrade of the previous high power laser systems at CUOS and consists of two beamlines thatoperate in perfect synchronization. The 500 TW beamline became operational in 2023, 2 PW operation started in 2025 and full 3 PW power levels will be available in 2026. It is presently the highest power laser system in the US. In this grant the high field science group at CUOS has leveraged this unique high power laser facility to investigate laser wake field acceleration (LWFA) in ultra-high power laser plasma interactions and have shown how this can scale for future electron–positron colliders at high energy. The dual beam experimental configuration enables flexibility for many frontier experiments in laser-driven acceleration research, in particular, enabling extended channelling/acceleration experiments, positron generation/acceleration experiments and proof-of-principle transverse pumping “dephasingless” electron acceleration experiment and theory. LWFA may be able to miniaturize particle accelerators for high energy physics and also enable new sources of ultrafast, extreme brightness and precise x-rays for a wide variety of applications. In laser wake field acceleration, an electron bunch “surfs” on the electron plasma wave (the “wake field”) generated by the ponderomotive force of an intense laser. The plasma wave has a strong longitudinal electric field that stays in phase with the relativistic driver. A relativistic charged particle may, therefore, remain in phase with the accelerating field over long distances and gain ultra-relativistic energies. The accelerating electric field strength that the plasma wave can support can be many orders of magnitude higher than that of conventional accelerators, which makes laser wakefield acceleration an exciting prospect as an advanced accelerator concept. In this research project we have investigated the scaling of this mechanism to laser powers of 2 PW and have measured the x-ray emission and radio frequency emission resulting from the acceleration process. We have also performed theoretical investigation of mechanisms to scale laser driven accelerators to much higher energy using dephasingless acceleration processes.

43 PARTICLE ACCELERATORS↗

Excitation of transverse dipole and quadrupole modes in a pure ion plasma in a linear Paul trap to study collective processes in intense beams

Transverse dipole and quadrupole modes have been excited in a one-component cesium ion plasma trapped in the Paul Trap Simulator Experiment (PTSX) in order to characterize their properties and understand the effect of their excitation on equivalent long-distance beam propagation. The PTSX device is a compact laboratory Paul trap that simulates the transverse dynamics of a long, intense charge bunch propagating through an alternating-gradient transport system by putting the physicist in the beam's frame of reference. A pair of arbitrary function generators was used to apply trapping voltage waveform perturbations with a range of frequencies and, by changing which electrodes were driven with the perturbation, with either a dipole or quadrupole spatial structure. The results presented in this paper explore the dependence of the perturbation voltage's effect on the perturbation duration and amplitude. Perturbations were also applied that simulate the effect of random lattice errors that exist in an accelerator with quadrupole magnets that are misaligned or have variance in their field strength. The experimental results quantify the growth in the equivalent transverse beam emittance that occurs due to the applied noise and demonstrate that the random lattice errors interact with the trapped plasma through the plasma's internal collective modes. Coherent periodic perturbations were applied to simulate the effects of magnet errors in circular machines such as storage rings. The trapped one component plasma is strongly affected when the perturbation frequency is commensurate with a plasma mode frequency. The experimental results, which help to understand the physics of quiescent intense beam propagation over large distances, are compared with analytic models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Integration of sensors through additive manufacturing leading to increased efficiencies of gas turbines for power generation and propulsion

To realize the full capability of additively manufactured components in complex energy systems, it is imperative to minimize early component failures during development phases and during operation. Traditional field feedback timelines and offline inspection protocols significantly reduce the design-manufacturing iteration times. To address this specific question, the project developed and demonstrated a method for the integration of sensors into complex components through additive manufacturing. The team used gas turbine engines as a platform, which meets the need of both power generation and propulsion and offer opportunities for cost reductions and efficiency increases. The innovation of this intelligent integration of sensors into complex components uniquely customized to address questions of integrity and durability for additively manufactured components. With real-time sensing data from additively manufactured components, turbine manufacturers will realize higher efficiencies, reduced component failures, and a 30-50% acceleration in product deployment of high efficiency gas turbine components due to a faster reduction in component risk assessment under actual operating conditions. This is a transformative shift towards a data-driven design and qualification of additively manufactured gas turbine components. To directly integrate sensors into additively manufactured components with all the complexities of actual hardware, powder bed fusion (direct metal laser sintering) and laser metal deposition technologies was developed. Validation took take place in two university laboratories both of which contain actual engine hardware and closely simulate a gas turbine prior to demonstrating the technology in a turbine development test. Indeed, two major technologies from this research cold impact turbine systems in the near future: (1) higher efficiency materials and designs enabled by additive manufacturing with 50% faster design to manufacturing cycle time, to enable faster time-to-market targets; and (2) integration of sensors into additively manufactured components enabling broad health and condition based prognostics for faster component and engine risk reduction.

33 ADVANCED PROPULSION SYSTEMS↗

The SLAC P2 Marx

A proposed high energy physics accelerator, the International Linear Collider, will require greater than five hundred rf stations. Each station is composed of a klystron driven by a modulator. Recently, the SLAC P2 Marx was designated the baseline modulator for the ILC. This paper describes some key features of this modulator and presents recent experimental results. The P2 Marx is presently being transported to another facility for lifetime testing. Here, we will gain understanding of how the Marx performs into a klystron load and gain experience operating the Marx for longer periods. Long term plans include the possibility of using this rf station for L-band technology demonstration at SLAC. While the Marx was designed with the ILC in mind, the topology can be readily applied to several different applications. We are currently evaluating the use of the topology for ESS, CLIC, and upgrades for systems at Fermi National Accelerator Laboratory. Because of the modular nature of the cell and the robustness of the control system, many different combinations of series and parallel operation are possible along with different load currents and pulse shapes.

43 PARTICLE ACCELERATORS↗

Survey of Dynamic Mode Decomposition Methods

Dynamic mode decomposition (DMD) is a data-driven reduced order modeling (ROM) technique used for dynamic systems. The widely adopted algorithm was first introduced and demonstrated on fluid flow data by Schmid. In recent years, various other fields, such as nuclear engineering, have begun to adopt this method. For example, DMD has been used for estimating α-eigenvalues, as an ROM for pulsed neutron problems, for predicting isotopic composition in burnup calculations, as acceleration techniques for iterative methods, and in capturing dynamic behaviors in molten salt reactor transients. This report seeks to demonstrate the capabilities and limits of the standard DMD algorithm, and identify problem spaces where variants may be better suited. The primary variant this report considers is Multi-Resolution DMD (mrDMD). Because this serves as a survey, synthetically produced data is used in lieu of simulation results. The remainder of this report will go into detail on the DMD theory, outline the standard DMD and mrDMD algorithms, present test cases highlighting the applicability of each, and finally present a discussion on how to determine the best suited algorithm for a given problem. All calculations performed in this report are carried out using the open source DMD library, PyDMD.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Motion of Air Bubbles in Water Subjected to Microgravity Accelerations

The International Space Station (ISS) serves as a platform for microgravity research for the foreseeable future. A microgravity environment is one in which the effects of gravity are drastically reduced which then allows physical experiments to be conducted without the overpowering effects of gravity. During his six month stay on the ISS, astronaut Donald R Pettit performed many informal/impromptu science experiments with available equipment. One such experiment focused on the motion of air bubbles in a rectangular container nearly filled with de-ionized water. Bubbles were introduced by shaking and the container was secured in place for several hours while motion of the bubbles were recorded using time-lapse photography. This paper shows correlation between bubble motion and quasi-steady acceleration levels during one such experiment operation. The quasi-steady acceleration vectors were measured by the Microgravity Acceleration Measurement System. Essentially linear motion was observed in the condition considered here. Dr. Pettit also created other conditions which produced linear and circulating motion, which are the subjects of further study. Initial observations of this bubble motion agree with calculations from many microgravity physical science experiments conducted on Shuttle microgravity science missions. Many crystal-growth furnaces involve heavy metals and high temperatures in which undesired acceleration-driven convection during solidification can adversely affect the crystal. Presented in this paper will be results showing correlation between bubble motion and the quasi-steady acceleration vector.

DeLombard, Richard↗

Machine learning-driven predictive resource management in complex science workflows

Here, the collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. Recently, advanced and complex data processing has gained increasing importance in science experiments. Data processing workflows typically consist of multiple intricate steps, and the precise specification of resource requirements is crucial for each step to allocate optimal resources for effective processing. Estimating resource requirements in advance is challenging due to a wide range of analysis scenarios, varying skill levels among community members, and the continuously increasing spectrum of computing options. One practical approach to mitigate these challenges involves initially processing a subset of each step to measure precise resource utilization from actual processing profiles before completing the entire step. While this two-staged approach enables processing on optimal resources for most of the workflow, it has drawbacks such as initial inaccuracies leading to potential failures and suboptimal resource usage, along with overhead from waiting for initial processing completion, which is critical for fast-turnaround analyses. In this context, our study introduces a novel pipeline of machine learning models within a comprehensive workflow management system, the Production and Distributed Analysis (PanDA) system. These models employ advanced machine learning techniques to predict key resource requirements, overcoming challenges posed by limited upfront knowledge of characteristics at each step. Accurate forecasts of resource requirements enable informed and proactive decision-making in workflow management, enhancing the efficiency of handling diverse, complex workflows across heterogeneous resources.

97 MATHEMATICS AND COMPUTING↗