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At least 217 records · Page 12

Analytical estimation of the signal to noise ratio efficiency in axion dark matter searches using a Savitzky-Golay filter

The signal to noise ratio efficiency ϵ SNR in axion dark matter searches has been estimated using large-statistic simulation data reflecting the background information and the expected axion signal power obtained from a real experiment. This usually requires a lot of computing time even with the assistance of powerful computing resources. Employing a Savitzky-Golay filter for background subtraction, in this work, we estimated a fully analytical ϵ SNR without relying on large-statistic simulation data, but only with an arbitrary axion mass and the relevant signal shape information. Hence, our work can provide ϵ SNR using minimal computing time and resources prior to the acquisition of experimental data, without the detailed information that has to be obtained from real experiments. Axion haloscope searches have been observing the coincidence that the frequency independent scale factor ξ is approximately consistent with the ϵ SNR . This was confirmed analytically in this work, when the window length of the Savitzky-Golay filter is reasonably wide enough, i.e., at least 5 times the signal window.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Adding a Second Ku-Band Antenna to the International Space Station

The International Space Station, as originally developed, used the Ku-Band Tracking and Data Relay Satellite System communications link to transmit non-critical data to the ground. Since becoming operational, the use for the link evolved to include additional services that, although also not critical, were deemed to be necessary for the crew. The external Ku-Band Antennas were designed for transport to the ISS in the shuttle cargo bay and thus are not suitable for manifesting on any current cargo vehicle. The original intent was to stow two spare antennas on orbit in a protective container until such time as they were needed to replace a failing unit which is a long and complicated process due to the complexity of the removal and replacement procedure. The Boeing Company proposed manifesting one of those spare antennas in an operable configuration eliminating the need for an Extravehicular Activity (EVA) to correct the first failure and as such minimizing the time to hours rather than weeks required to restore the Ku-Band communications link after failures. After the first failure, an EVA would be scheduled to replace the failed antenna with the stowed spare antenna. Because the hot spare is activated internal to the ISS, the replacement of the failed unit can be done when convenient rather than in haste. This paper describes the methodology used to locate a suitable site to add a new antenna mast to the ISS as well the process followed to fabricate, deliver and install the new interface hardware. Because this was not planned when the ISS was originally designed, structural, power, data and Intermediate Frequency signal connections had to be found for use. With the movement of the P6 solar array element from the initial location in the center zenith location of the ISS to the end of the port side of the truss and concurrent relocation of one string of S-Band communications assets, there were candidate power, data and structural connections available on the Z1 Truss. The engineering team evaluated these residual interfaces for use and designed cabling and structural elements for the candidate interfaces. The antenna was recently installed on ULF-4 and has completed a preliminary checkout. Included in this check out were evaluation of the power level received from the TDRS and evaluation of the gimbal position feedback for consideration in the static bias pointing matrix. This process demonstrates the ability to modify and upgrade manned space vehicles as either need or technology requires.

DuSold, Chuck↗

Structure-Driven Liquid Microjunction Surface-Sampling Probe Mass Spectrometry

The rhizosphere is the narrow region of soil surrounding the roots of plants that is influenced by root exudates, root secretions, and associated microbial communities. This region is crucial to plant growth and development and plays a critical role in nutrient uptake, disease resistance, and soil transformation. Understanding the function of exogenous compounds in the rhizosphere starts with determining the spatiotemporal distribution of these molecular components. Using liquid microjunction surface-sampling probe mass spectrometry (LMJ-SSP-MS) and microfluidic devices with attached microporous membranes enables in situ, nondisruptive, and nondestructive spatiotemporal measurement of exogenous compounds from plant roots. However, long imaging times (>2 h) can negatively affect plant heath and limit temporal studies. Here, we present a novel strategy to optimize the number and location of sampling sites on these microporous membrane-covered microfluidic devices. In conclusion, this novel, “structure-driven” sampling workflow takes into consideration the channel structure of the microfluidic device to maximize sampling from the channels and minimize acquisition time (~4× less time in some cases while providing similar chemical image accuracy), thus reducing stress on plants during in situ LMJ-SSP-MS analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Turnaround Time Modeling for Conceptual Rocket Engines

Recent years have brought about a paradigm shift within NASA and the Space Launch Community regarding the performance of conceptual design. Reliability, maintainability, supportability, and operability are no longer effects of design; they have moved to the forefront and are affecting design. A primary focus of this shift has been a planned decrease in vehicle turnaround time. Potentials for instituting this decrease include attacking the issues of removing, refurbishing, and replacing the engines after each flight. less, it is important to understand the operational affects of an engine on turnaround time, ground support personnel and equipment. One tool for visualizing this relationship involves the creation of a Discrete Event Simulation (DES). A DES model can be used to run a series of trade studies to determine if the engine is meeting its requirements, and, if not, what can be altered to bring it into compliance. Using DES, it is possible to look at the ways in which labor requirements, parallel maintenance versus serial maintenance, and maintenance scheduling affect the overall turnaround time. A detailed DES model of the Space Shuttle Main Engines (SSME) has been developed. Trades may be performed using the SSME Processing Model to see where maintenance bottlenecks occur, what the benefits (if any) are of increasing the numbers of personnel, or the number and location of facilities, in addition to trades previously mentioned, all with the goal of optimizing the operational turnaround time and minimizing operational cost. The SSME Processing Model was developed in such a way that it can easily be used as a foundation for developing DES models of other operational or developmental reusable engines. Performing a DES on a developmental engine during the conceptual phase makes it easier to affect the design and make changes to bring about a decrease in turnaround time and costs.

Nix, Michael↗

Urban Air Mobility Network and Vehicle Type - Modeling and Assessment

This paper describes exploratory modeling of an on-demand urban air mobility (UAM) network and sizing of vehicles to operate within that network. UAM seeks to improve the movement of goods and people around a metropolitan area by utilizing the airspace for transport. Aircraft sizing and overall network performance results are presented that include comparisons of battery-electric and various hybrid-electric vehicles that are fueled with diesel, jet fuel, compressed natural gas, and liquefied natural gas (LNG). Hybrid-electric propulsion systems consisting of internal combustion engine-generators, turbine-generators, and solid oxide fuel cells are explored. Ultimately, the "performance" of the UAM network over a day for each of the different vehicle types, propulsion systems, and stored energy sources is described in four parameters: 1) the average cost per seat-kilometer, which considers the costs of the energy/fuel, vehicle acquisition, insurance, maintenance, pilot, and battery replacement costs, 2) carbon dioxide emission rates associated with vehicle operations, 3) the average passenger wait time, and 4) the average load factor, i.e., the total number of seats filled with paying passengers divided by the total number of available seats. Results indicate that the "dispatch model," which determines when and where aircraft are flown around the UAM network, is critical in determining the overall network performance. This is due to the often-conflicting desires to allow passengers to depart with minimal wait time while still maintaining a high load factor to reduce operating costs. Additionally, regardless of the dispatch model, hybrid-electric aircraft powered by internal combustion engines fueled with diesel or LNG are consistently the lowest cost per seat-kilometer. Battery-electric and future technology LNG/solid oxide fuel cell aircraft produce the lowest emissions (assuming the California grid) with LNG-fueled internal combustion engine-powered hybrids producing only slightly more carbon dioxide.

Assessment↗

Unified differentiable digital twin for the IOTA/FAST facility

As the design complexity of modern accelerators grows, there is more interest in using advanced simulations that have fast execution time or produce insights about accelerator state. One notable example of additional information are gradients of physical observables with respect to design parameters produced by differentiable simulations. The IOTA/FAST facility has recently begun a program to implement and experimentally validate a unified start-to-end differentiable digital twin to serve as a virtual accelerator test stand, allowing for rapid prototyping of new software and experiments with minimal beam time costs. In this contribution we will discuss our plans and progress. Specifically, we will cover the selection and benchmarking of both physics and ML codes, the development of generic interfaces between device models and surrogate or physics-based sections, and the export of the parameters through either a deterministic event loop or a fully asynchronous EPICS soft input/output controller. We will also discuss challenges in model calibration and uncertainty quantification, as well as future plans to support larger proton accelerators like PIPII and Booster.

Kuklev, Nikita [Fermilab]↗

End-to-end differentiable digital twin for the IOTA/FAST facility

As the design complexity of modern accelerators grows, there is more interest in using controllable-fidelity simulations that have fast execution time or can yield additional insights about accelerator state. One notable example of additional information are gradients of physical observables with respect to design parameters produced by differentiable simulations. The IOTA/FAST facility has recently begun a program to implement and experimentally validate an end-to-end digital twin to serve as a virtual accelerator test stand, allowing for rapid prototyping of new software and experiments with minimal beam time costs. In this contribution we will discuss our plans and progress. Specifically, we will cover the selection and benchmarking of both physics and ML codes for linac and ring simulation, the development of generic interfaces between surrogate and physics-based sections, and presenting the control interface as either a deterministic event loop or a fully asynchronous EPICS soft input/output controller. We will also discuss challenges in model calibration and uncertainty quantification, as well as future plans to implement larger proton accelerators like PIPII and Booster.

Kuklev, N. [Fermilab]↗

Team X Spacecraft Instrument Database Consolidation

In the past decade, many changes have been made to Team X's process of designing each spacecraft, with the purpose of making the overall procedure more efficient over time. One such improvement is the use of information databases from previous missions, designs, and research. By referring to these databases, members of the design team can locate relevant instrument data and significantly reduce the total time they spend on each design. The files in these databases were stored in several different formats with various levels of accuracy. During the past 2 months, efforts have been made in an attempt to combine and organize these files. The main focus was in the Instruments department, where spacecraft subsystems are designed based on mission measurement requirements. A common database was developed for all instrument parameters using Microsoft Excel to minimize the time and confusion experienced when searching through files stored in several different formats and locations. By making this collection of information more organized, the files within them have become more easily searchable. Additionally, the new Excel database offers the option of importing its contents into a more efficient database management system in the future. This potential for expansion enables the database to grow and acquire more search features as needed.

Wallenstein, Kelly A.↗

Electronic Structure Theory Calculations Using Modern Architectures: KNL vs Haswell

The time to solution and parallel efficiency of several commonly used electronic structure methods (Hartree–Fock, density functional theory, second order perturbation theory, resolution of the identity second order perturbation theory, coupled cluster) are evaluated on both the Intel Xeon Haswell and the Intel Xeon Phi Knights Landing (KNL) architectures. The Haswell completes the benchmark calculations with a faster time to solution than the KNL for all molecules and methods tested. While the Haswell exhibits an average speedup of at least 3.5 relative to the KNL for all nonthreaded computations, the KNL has a better parallel efficiency than the Haswell with increasing core counts. The architectures are further tested using a more computationally costly coupled cluster method on a transition state reaction. The Haswell appears to be the best choice to minimize the time to solution, though for very large systems and high levels of theory that require memory intensive processes the superior memory hierarchy and larger on node memory of the KNL can make it a better choice. These results are used to showcase aspects of novel architectures that will increase efficiency for quantum chemistry applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sustainability of the Catalytic Activity of a Silica-Titania Composite (STC) for Long-Term Indoor Air Quality Control

TiO2-assisted photocatalytic oxidation (PCO) is an emerging technology for indoor air quality control and is also being evaluated as an alternative trace contaminant control technology for crew habitats in space exploration. Though there exists a vast range of literature on the development of photocatalysts and associated reactor systems, including catalyst performance and performance-influencing factors, the critical question of whether photocatalysts can sustain their initial catalytic activity over an extended period of operation has not been adequately addressed. For a catalyst to effectively serve as an air quality control product, it must be rugged enough to withstand exposure to a multitude of low concentration volatile organic compounds (VOCs) over long periods of time with minimal loss of activity. The objective of this study was to determine the functional lifetime of a promising photocatalyst - the silica-titania composite (STC) from Sol Gel Solutions, LLC in a real-world scenario. A bench-scale STC-packed annular reactor under continuous irradiation by a UV-A fluorescent black-light blue lamp ((lambda)max = 365 nm) was exposed to laboratory air continuously at an apparent contact time of 0.27 sand challenged with a known concentration of ethanol periodically to assess any changes in catalytic activity. Laboratory air was also episodically spiked with halocarbons (e.g., octafluoropropane), organosulfur compounds (e.g., sulfur hexafluoride), and organosilicons (e.g., siloxanes) to simulate accidental releases or leaks of such VOCs. Total organic carbon (TOC) loading and contaminant profiles of the laboratory air were also monitored. Changes in STC photocatalytic performance were evaluated using the ethanol mineralization rate, mineralization efficiency, and oxidation intermediate (acetaldehyde) formation. Results provide insights to any potential catalyst poisoning by trace halocarbons and organosulfur compounds.

Coutts, Janelle L.↗

Optimizing Performance on Trinity Utilizing Machine Learning, Proxy Applications and Scheduling Priorities

The sheer number of nodes continues to increase in today’s supercomputers, the first half of Trinity alone contains more than 9400 compute nodes. Since the speed of today’s clusters are limited by the slowest nodes, it more important than ever to identify slow nodes, improve their performance if it can be done, and assure minimal usage of slower nodes during performance critical runs. This is an ongoing maintenance task that occurs on a regular basis and, therefore, it is important to minimize the impact upon its users by assessing and addressing slow performing nodes and mitigating their consequences while minimizing down time. These issues can be solved, in large part, through a systematic application of fast running hardware assessment tests, the application of Machine Learning, and making use of performance data to increase efficiency of large clusters. Proxy applications utilizing both MPI and OpenMP were developed to produce data as a substitute for long runtime applications to evaluate node performance. Machine learning is applied to identify underperforming nodes, and policies are being discussed to both minimize the impact of underperforming nodes and increase the efficiency of the system. In this paper, I will describe the process used to produce quickly performing proxy tests, consider various methods to isolate the outliers, and produce ordered lists for use in scheduling to accomplish this task.

97 MATHEMATICS AND COMPUTING↗

Substrate Effects When Using Photons to Make Perovskite Solar Cells

To shorten annealing time and minimize substrate heating, flash lamps that deliver short, intense light pulses, commonly called photonic curing, are used to replace thermal annealing using hot plates or ovens. This method is different from equilibrium heating in that the radiant energy is selectively absorbed by the film. The high-intensity light pulses produce a high peak temperature in the film. Because most processes follow Arrhenius behavior, reaching high temperatures allow chemical reactions/phase transformations to occur in a short time, significantly reducing the processing time. Often the results are non-intuitive. We will present fabricating flexible halide perovskite solar cells (PSCs) on indium tin oxide (ITO) coated Willow glass. The effect of ITO transmittance on the photonic curing of nickel nitrate sol-gel precursors into nickel oxide to fabricate hole transport layer and consequently the performance of PSCs. Unexpectedly, ITO samples processed by photonic curing show improved optical and electrical properties.

14 SOLAR ENERGY↗

Fault Tree Based Diagnosis with Optimal Test Sequencing for Field Service Engineers

When field service engineers go to customer sites to service equipment, they want to diagnose and repair failures quickly and cost effectively. Symptoms exhibited by failed equipment frequently suggest several possible causes which require different approaches to diagnosis. This can lead the engineer to follow several fruitless paths in the diagnostic process before they find the actual failure. To assist in this situation, we have developed the Fault Tree Diagnosis and Optimal Test Sequence (FTDOTS) software system that performs automated diagnosis and ranks diagnostic hypotheses based on failure probability and the time or cost required to isolate and repair each failure. FTDOTS first finds a set of possible failures that explain exhibited symptoms by using a fault tree reliability model as a diagnostic knowledge to rank the hypothesized failures based on how likely they are and how long it would take or how much it would cost to isolate and repair them. This ordering suggests an optimal sequence for the field service engineer to investigate the hypothesized failures in order to minimize the time or cost required to accomplish the repair task. Previously, field service personnel would arrive at the customer site and choose which components to investigate based on past experience and service manuals. Using FTDOTS running on a portable computer, they can now enter a set of symptoms and get a list of possible failures ordered in an optimal test sequence to help them in their decisions. If facilities are available, the field engineer can connect the portable computer to the malfunctioning device for automated data gathering. FTDOTS is currently being applied to field service of medical test equipment. The techniques are flexible enough to use for many different types of devices. If a fault tree model of the equipment and information about component failure probabilities and isolation times or costs are available, a diagnostic knowledge base for that device can be developed easily.

Iverson, David L.↗

The DESC stellarator code suite Part 3: Quasi-symmetry optimization

The DESC stellarator optimization code takes advantage of advanced numerical methods to search the full parameter space much faster than conventional tools. Only a single equilibrium solution is needed at each optimization step thanks to automatic differentiation, which efficiently provides exact derivative information. A Gauss–Newton trust-region optimization method uses second-order derivative information to take large steps in parameter space and converges rapidly. With just-in-time compilation and GPU portability, high-dimensional stellarator optimization runs take orders of magnitude less computation time with DESC compared to other approaches. This paper presents the theory of the DESC fixed-boundary local optimization algorithm along with demonstrations of how to easily implement it in the code. Example quasi-symmetry optimizations are shown and compared to results from conventional tools. Three different forms of quasi-symmetry objectives are available in DESC, and their relative advantages are discussed in detail. In the examples presented, the triple product formulation yields the best optimization results in terms of minimized computation time and particle transport. This paper concludes with an explanation of how the modular code suite can be extended to accommodate other types of optimization problems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Mirror fusion propulsion system - A performance comparison with alternate propulsion systems for the manned Mars mission

The performance characteristics of several propulsion technologies applied to piloted Mars missions are compared. The characteristics that are compared are Initial Mass in Low Earth Orbit (IMLEO), mission flexibility, and flight times. The propulsion systems being compared are both demonstrated and envisioned: Chemical (or Cryogenic), Nuclear Thermal Rocket (NTR) solid core, NTR gas core, Nuclear Electric Propulsion (NEP), and a mirror fusion space propulsion system. The proposed magnetic mirror fusion reactor, known as the Mirror Fusion Propulsion System (MFPS), is described. The description is an overview of a design study that was conducted to convert a mirror reactor experiment at Lawrence Livermore National Lab (LLNL) into a viable space propulsion system. Design principles geared towards minimizing mass and maximizing power available for thrust are identified and applied to the LLNL reactor design, resulting in the MFPS. The MFPS' design evolution, reactor and fuel choices, and system configuration are described. Results of the performance comparison shows that the MFPS minimizes flight time to 60 to 90 days for flights to Mars while allowing continuous return-home capability while at Mars. Total MFPS IMLEO including propellant and payloads is kept to about 1,000 metric tons.

Deveny, M.↗

Mirror fusion propulsion system: A performance comparison with alternate propulsion systems for the manned Mars Mission

The performance characteristics of several propulsion technologies applied to piloted Mars missions are compared. The characteristics that are compared are Initial Mass in Low Earth Orbit (IMLEO), mission flexibility, and flight times. The propulsion systems being compared are both demonstrated and envisioned: Chemical (or Cryogenic), Nuclear Thermal Rocket (NTR) solid core, NTR gas core, Nuclear Electric Propulsion (NEP), and a mirror fusion space propulsion system. The proposed magnetic mirror fusion reactor, known as the Mirror Fusion Propulsion System (MFPS), is described. The description is an overview of a design study that was conducted to convert a mirror reactor experiment at Lawrence Livermore National Lab (LLNL) into a viable space propulsion system. Design principles geared towards minimizing mass and maximizing power available for thrust are identified and applied to the LLNL reactor design, resulting in the MFPS. The MFPS' design evolution, reactor and fuel choices, and system configuration are described. Results of the performance comparison shows that the MFPS minimizes flight time to 60 to 90 days for flights to Mars while allowing continuous return-home capability while at Mars. Total MFPS IMLEO including propellant and payloads is kept to about 1,000 metric tons.

Schulze, Norman R.↗

Impact of Flow Configurations on Response Time and Data Quality in Real-Time, In-Line Fourier Transform Infrared (FTIR) Monitoring of Viscous Flows

The real-time, in-line monitoring of continuous flow concentrations is widely conducted via infrared (IR) spectrometry by using a flow cell connected to a reactive flow stream. For protective purposes, the IR sensor tip is typically offset from the flow. This offset can cause the formation of a stagnant boundary layer above the sensor, especially when dealing with high-viscosity fluids. As a result, the IR signal response time is often controlled by the slow diffusional exchange of fluid in the boundary layer, as confirmed via 2D computational fluid dynamics (CFD) simulations. We evaluated several flow configuration modifications in a typical IR flow cell in order to identify the changes to the flow dynamics that enable improved response times with minimal changes to the cell configuration: the use of (i) vertical flow, where the standard horizontal flow over the sensor is redirected to contact vertically with the sensor, (ii) a static mixer to create radial flow momentum above the IR sensor, and (iii) horizontal or vertical nozzles to direct the flow toward the IR sensor. The vertical flow configuration did not show any significant improvement over the standard horizontal flow configuration. However, the static mixer, horizontal nozzle, and vertical nozzle configurations all resulted in markedly improved response times and signal quality, albeit at the expense of a higher pressure drop across the flow cell. These results point toward straightforward, user-accessible modifications of in-line IR flow cells that result in significant improvements in signal stability and acquisition times.

42 ENGINEERING↗

Benchmarking universal machine learning interatomic potentials for rapid analysis of inelastic neutron scattering data

The accurate calculation of phonons and vibrational spectra remains a significant challenge, requiring highly precise evaluations of interatomic forces. Traditional methods based on the quantum description of the electronic structure, while widely used, are computationally expensive and demand substantial expertise. Emerging universal machine learning interatomic potentials (uMLIPs) offer a transformative alternative by employing pre-trained neural network surrogates to predict interatomic forces directly from atomic coordinates. This approach dramatically reduces computation time and minimizes the need for technical knowledge. In this paper, we produce a phonon database comprising nearly 5000 inorganic crystals to benchmark the performance of several leading uMLIPs. We further assess these models in real-world applications by using them to analyze experimental inelastic neutron scattering data collected on a variety of materials. Through detailed comparisons, we identify the strengths and limitations of these uMLIPs, providing insights into their accuracy and suitability for fast calculations of phonons and related properties, as well as the potential for real-time interpretation of neutron scattering spectra. Our findings highlight how the rapid advancement of AI in science is revolutionizing experimental research and data analysis.

inelastic neutron scattering↗