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At least 1,369 records · Page 76

Spherical tokamak physics research in preparation for the operation of NSTX-U

The National Spherical Torus Experiment Upgrade (NSTX-U) is preparing to resume operation, representing a crucial step toward realizing compact, cost-effective fusion pilot plants. In advance of this, extensive modeling and data analysis have been conducted to advance the physics basis for low-aspect-ratio, high-performance plasma regimes, focusing on three core objectives: confinement and stability, power and particle handling, and steady-state operation. Significant progress has been made in understanding the electron temperature flattening in high-β plasmas, which is shown to be driven by a complex interplay of magnetohydrodynamic instabilities (e.g. non-resonant infernal modes), fast-ion-driven Alfvén eigenmodes, and electron and ion-scale micro-instabilities, particularly Kinetic Ballooning Modes (KBMs), whose destabilization is strongly dependent on parallel magnetic field fluctuations (δB ∥ ). Furthermore, a new gyrokinetic critical pedestal model was developed, accurately predicting pedestal structure by identifying KBMs as the primary stability limit, offering a critical constraint for future high-confinement scenarios. To address the challenge of high heat flux, novel liquid lithium plasma-facing components were modeled. The analysis confirmed that lithium vapor shielding is a self-regulating mechanism for heat mitigation, while also emphasizing that strong main ion parallel flow is essential to minimize core lithium contamination. Finally, progress toward steady-state operation was anchored by developing the required physics basis and control tools. This includes predictive modeling for reversed magnetic shear sustainment, demonstrating that magnetic island-induced bootstrap current reduction is negligible in STs, and advancing real-time control and disruption avoidance capabilities. The development of high-speed surrogate models (e.g. MMMNet) provides computationally efficient tools vital for non-inductive scenario optimization and integrated, low-disruptivity operations planned for NSTX-U.

NSTX-U↗

Electromagnetic physics models for parallel computing architectures

The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part of the GeantV project. Finally, the results of preliminary performance evaluation and physics validation are presented as well.

97 MATHEMATICS AND COMPUTING↗

Key Learnings from Hydraulic Fracturing Test Site - 2 (HFTS-2), Delaware Basin

Hydraulic fractures (HF) play a dominant role in oil and gas production from unconventional reservoirs, fracture characteristics, geometry, and extent are generally not well known and are typically inferred from various monitoring methods or subsurface models. The Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp formation of the Permian (Delaware) Basin. HFTS-2, a unique joint industry program (JIP) that brings together government, academia, and industry, focused on field data acquisition and interpretation. The project has built a comprehensive HF research dataset that includes microseismic (MS), 1,500 ft of core, diagnostic formation injection tests (DFIT), fluid characterization, advanced logs, geochemistry, downhole gauges, varying completions, and permanent fiber optic (FO) cable in vertical and horizontal wells. These data were integrated and used to characterize HF geometry/dimensions and resulting depletion profiles, gain insights for completion design, and achieve a better understanding of parent well depletion effects on child well performance. The analysis and integration of the comprehensive HFTS-2 diagnostics dataset provide insights for optimal well placement and completions and improves understanding about the effects of parent well depletion. Furthermore, this dataset can be used to blind test and develop subsurface workflows for unconventional resources. Key learnings from HFTS-2 and the new technologies tested can easily be transferred to other unconventional plays.

58 GEOSCIENCES↗

Acoustic modal analysis of a full-scale annular combustor

An acoustic modal decomposition of the measured pressure field in a full scale annular combustor installed in a ducted test rig is described. The modal analysis, utilizing a least squares optimization routine, is facilitated by the assumption of randomly occurring pressure disturbances which generate equal amplitude clockwise and counter-clockwise pressure waves, and the assumption of statistical independence between modes. These assumptions are fully justified by the measured cross spectral phases between the various measurement points. The resultant modal decomposition indicates that higher order modes compose the dominant portion of the combustor pressure spectrum in the range of frequencies of interest in core noise studies. A second major finding is that, over the frequency range of interest, each individual mode which is present exists in virtual isolation over significant portions of the spectrum. Finally, a comparison between the present results and a limited amount of data obtained in an operating turbofan engine with the same combustor is made. The comparison is sufficiently favorable to warrant the conclusion that the structure of the combustor pressure field is preserved between the component facility and the engine.

Karchmer, A. M.↗

Acoustic modal analysis of a full-scale annular combustor

An acoustic modal decomposition of the measured pressure field in a full scale annular combustor installed in a ducted test rig is described. The modal analysis, utilizing a least squares optimization routine, is facilitated by the assumption of randomly occurring pressure disturbances which generate equal amplitude clockwise and counter-clockwise pressure waves, and the assumption of statistical independence between modes. These assumptions are fully justified by the measured cross spectral phases between the various measurement points. The resultant modal decomposition indicates that higher order modes compose the dominant portion of the combustor pressure spectrum in the range of frequencies of interest in core noise studies. A second major finding is that, over the frequency range of interest, each individual mode which is present exists in virtual isolation over significant portions of the spectrum. Finally, a comparison between the present results and a limited amount of data obtained in an operating turbofan engine with the same combustor is made. The comparison is sufficiently favorable to warrant the conclusion that the structure of the combustor pressure field is preserved between the component facility and the engine. Previously announced in STAR as N83-21896

Karchmer, A. M.↗

Applications of Dynamic Land Surface Information for Passive Microwave Precipitation Retrieval

Accurate, physically based precipitation retrieval over global land surfaces is an important goal of the NASA/JAXA Global Precipitation Measurement Mission (GPM). This is a difficult problem for the passive microwave constellation, as the signal over radiometrically warm land surfaces in the microwave frequencies means that the measurements used are indirect and typically require inferring some type of relationship between an observed scattering signal and precipitation at the surface. GPM, with collocated radiometer and dual-frequency radar, is an excellent tool for tackling this problem and improving global retrievals. In the years following the launch of the GPM Core Observatory satellite, physically based passive microwave retrieval of precipitation over land continues to be challenging. Validation efforts suggest that the operational GPM passive microwave algorithm, the Goddard profiling algorithm (GPROF), tends to overestimate precipitation at the low (<5 mm h−1) end of the distribution over land. In this work, retrieval sensitivities to dynamic surface conditions are explored through enhancement of the algorithm with dynamic, retrieved information from a GPM-derived optimal estimation scheme. The retrieved parameters describing surface and background characteristics replace current static or ancillary GPROF information including emissivity, water vapor, and snow cover. Results show that adding this information decreases probability of false detection by 50% and, most importantly, the enhancements with retrieved parameters move the retrieval away from dependence on ancillary datasets and lead to improved physical consistency.

Sarah Ringerud↗

Multi-agent AI collaboration for digital twin development and assessment

Developing a digital twin (DT) model involves different steps that encompass formulating requirements, model development, implementation, and assessment with respect to real applications. Human expertise is required to coordinate and implement different steps in the DT development and assessment process. However, certain parts of this process can be automated using artificial intelligence (AI) agents for efficient workflow development. In this work, we test and analyze a multiagent AI collaboration with humans in the loop to automate different elements of the DT development and assessment process. To implement the workflow for multiagent AI DT development and assessment, we use Autogen, a multiagent framework developed by Microsoft. Autogen offers a modular and flexible framework for configuring and designing task-specific multiagent workflows. In this framework, large language models (LLMs) form the core intelligence of the AI agents where the quality and performance of the automated element is governed by the inherent capabilities and knowledge base of the LLM. We use retrieval augmented generation to supplement the LLM with relevant domain-specific information for DT requirement formulation. We illustrate this multiagent workflow using a case study on a thermal energy storage system, focusing on how AI agents can collaborate with humans to expedite and optimize different elements of DT development and assessment process.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Significant Efficiency Enhancements in Non‐Y Series Acceptors by the Addition of Outer Side Chains

Abstract Most current highly efficient organic solar cells utilize small molecules like Y6 and its derivatives as electron acceptors in the photoactive layer. In this work, a small molecule acceptor, SC8‐IT4F, is developed through outer side chain engineering on the terminal thiophene of a conjugated 6,12‐dihydro‐dithienoindeno[2,3‐d:2′,3′‐d′]‐s‐indaceno[1,2‐b:5,6‐b′]dithiophene (IDTT) central core. Compared to the reference molecule C8‐IT4F, which lacks outer side chains, SC8‐IT4F displays notable differences in molecule geometry (as shown by simulations), thermal behavior, single‐crystal packing, and film morphology. Blend films of SC8‐IT4F and the polymer donor PM6 exhibit larger carrier mobilities, longer carrier lifetimes, and reduced recombination compared to C8‐IT4F, resulting in improved device performance. Binary photovoltaic devices based on the PM6:SC8‐IT4F films reveal an optimal efficiency over 15%, which is one of the best values for non‐Y type small molecule acceptors (SMAs). The resultant devices also show better thermal and operational stability than the control PM6:L8‐BO devices. SC8‐IT4F and its blend exhibit a higher relative degree of crystallinity and π coherence length, compared to C8‐IT4F samples, beneficial for charge transport and device performance. The results indicate that outer side chain engineering on existing small electron acceptors can be a promising molecular design strategy for further pursuing high‐performance organic solar cells.

He, Qiao [Department of Chemistry and Centre for P↗

Efficient algorithms and implementations of entropy-based moment closures for rarefied gases

We present efficient algorithms and implementations of the 35-moment system equipped with the maximum-entropy closure in the context of rarefied gases. While closures based on the principle of entropy maximization have been shown to yield very promising results for moderately rarefied gas flows, the computational cost of these closures is in general much higher than for closure theories with explicit closed-form expressions of the closing fluxes, such as Grad's classical closure. Following a similar approach as Garrett et al. (2015) , we investigate efficient implementations of the computationally expensive numerical quadrature method used for the moment evaluations of the maximum-entropy distribution by exploiting its inherent fine-grained parallelism with the parallelism offered by multi-core processors and graphics cards. We show that using a single graphics card as an accelerator allows speed-ups of two orders of magnitude when compared to a serial CPU implementation. To accelerate the time-to-solution for steady-state problems, we propose a new semi-implicit time discretization scheme. The resulting nonlinear system of equations is solved with a Newton type method in the Lagrange multipliers of the dual optimization problem in order to reduce the computational cost. Additionally, fully explicit time-stepping schemes of first and second order accuracy are presented. We investigate the accuracy and efficiency of the numerical schemes for several numerical test cases, including a steady-state shock-structure problem.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

UNRAVEL: A Robust Modular Velocity Dealiasing Technique for Doppler Radar

Unfold Radar Velocity (UNRAVEL) is an open-source modular Doppler velocity dealiasing algorithm for weather radars. UNRAVEL is an algorithm that does not need external reference velocity data, making it easily applicable. The proposed algorithm includes 11 core modules and 2 dealiasing strategies. UNRAVEL is an iterative algorithm. The goal is to build the dealiasing results starting with the strictest possible continuity tests in azimuth and range and, after each step, relaxing the parameters to include more results from a progressively growing number of reference points. UNRAVEL also has modules that perform 3D continuity checks. Thanks to this modular design, the number of dealiasing strategies can be expanded in order to optimize the dealiasing results. While the first driver dealiases Doppler velocity from each tilt independently from one another, the second driver also performs a three-dimensional continuity check of the velocity using successive elevations. The proposed dealiasing algorithm is tested using severe weather data from an S-band Doppler radar that have been aliased to mimic aliased radial velocity patterns that would be observed by a C-band Doppler radar. Artificially aliasing S-band data permits creation of a reference to which the performance of various dealiasing techniques can be compared. Comparisons show that UNRAVEL consistently outperforms other established dealiasing algorithms for the test period selected in this work.

47 OTHER INSTRUMENTATION↗

Projected Cosmological Constraints from Strongly Lensed Supernovae with the Roman Space Telescope

One of the primary mission objectives of the Roman Space Telescope is to investigate the nature of dark energy with a variety of methods. Observations of Type I supernovae (SNe Ia) will be one of the principal anchors of the Roman cosmology program through traditional luminosity distance measurements. This SNe Ia cosmology program can provide another valuable cosmological probe, without altering the strategy of the mission: time delay cosmography with gravitationally lensed supernova (SN). In this work, we forecast lensed SN cosmology constraints with the Roman Space Telescope, while providing useful tools for future work. Using the anticipated characteristics of the Roman SNe Ia survey, we have constructed mock catalogs of expected resolved lensing systems, as well as strongly lensed Type Ia and core-collapse (CC) SN light curves, including microlensing effects. We predict Roman will find ~11 lensed SNe Ia and ~20 CCSNe, depending on the survey strategy. Next, we estimate the time delay precision obtainable with Roman (Ia: ~2 days, CC: ~3 days), and use a Fisher matrix analysis to derive projected constraints on H 0 ,Ω m , and the dark energy equation of state, w, for each SNe Ia survey strategy. Here, a strategy optimized for the discovery of high-redshift SNe Ia is preferred when considering the constraints possible from both SNe Ia and lensed SN cosmology, also delivering ~1.5 times more lensed SNe than other proposed survey strategies.

79 ASTRONOMY AND ASTROPHYSICS↗

High pressure compressor component performance report

A compressor optimization study defined a 10 stage configuration with a 22.6:1 pressure ratio, an adiabatic efficiency goal of 86.1%, and a polytropic efficiency of 90.6%; the corrected airflow is 53.5 kg/s. Subsequent component testing included three full scale tests: a six stage rig test, a 10 stage rig test, and another 10 stage rig test completed in the second quarter of 1982. Information from these tests is used to select the configuration for a core engine test and an integrated core/low spool test. The test results will also provide data base for the flight propulsion system. The results of the test series with both aerodynamic and mechanical performance of each compressor build are presented. The second 10 stage compressor adiabatic efficiency was 0.848 at a cruise operating point versus a test goal of 0.846.

Cline, S. J.↗

RIACS/USRA

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on 6 June 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. A flexible scientific staff is provided through a university faculty visitor program, a post doctoral program, and a student visitor program. Not only does this provide appropriate expertise but it also introduces scientists outside of NASA to NASA problems. A small group of core RIACS staff provides continuity and interacts with an ARC technical monitor and scientific advisory group to determine the RIACS mission. RIACS activities are reviewed and monitored by a USRA advisory council and ARC technical monitor. Research at RIACS is currently being done in the following areas: Parallel Computing, Advanced Methods for Scientific Computing, High Performance Networks and Technology, and Learning Systems. Parallel compiler techniques, adaptive numerical methods for flows in complicated geometries, and optimization were identified as important problems to investigate for ARC's involvement in the Computational Grand Challenges of the next decade.

Oliger, Joseph↗

m-CUBES An efficient and portable implementation of multi-dimensional integration for gpus

The task of multi-dimensional numerical integration is frequently encountered in physics and other scientific fields, e.g., in modeling the effects of systematic uncertainties in physical systems and in Bayesian parameter estimation. Multi-dimensional integration is often time-prohibitive on CPUs. Efficient implementation on many-core architectures is challenging as the workload across the integration space cannot be predicted a priori. We propose m-Cubes, a novel implementation of the well-known Vegas algorithm for execution on GPUs. Vegas transforms integration variables followed by calculation of a Monte Carlo integral estimate using adaptive partitioning of the resulting space. m-Cubes improves performance on GPUs by maintaining relatively uniform workload across the processors. As a result, our optimized Cuda implementation for Nvidia GPUs outperforms parallelization approaches proposed in past literature. We further demonstrate the efficiency of m-Cubes by evaluating a six-dimensional integral from a cosmology application, achieving significant speedup and greater precision than the CUBA library's CPU implementation of VEGAS. We also evaluate m-Cubes on a standard integrand test suite. m-Cubes outperforms the serial implementations of the Cuba and GSL libraries by orders of magnitude speedup while maintaining comparable accuracy. Our approach yields a speedup of at least 10 when compared against publicly available Monte Carlo based GPU implementations. In summary, m-Cubes can solve integrals that are prohibitively expensive using standard libraries and custom implementations. A modern C++ interface header-only implementation makes m-Cubes portable, allowing its utilization in complicated pipelines with easy to define stateful integrals. Compatibility with non-Nvidia GPUs is achieved with our initial implementation of m-Cubes using the Kokkos framework.

Sakiotis, Ioannis↗

Potent HIV‑1 protease inhibitors containing oxabicyclo octanol-derived P2-ligands: Design, synthesis, and X‑ray structural studies of inhibitor-HIV-1 protease complexes

Here, we describe here the design, synthesis, and X-ray structural studies of a new class of HIV-1 protease inhibitors containing 8-oxabicyclo[3.2.1]octanol-derived P2 ligands. We investigated the functional effect of these stereochemically defined fused-poly cyclic ligands on enzyme inhibition and antiviral activity in MT-2 cells. The tricyclic core of 8-oxabicyclo[3.2.1]octan-6-ol is designed to interact with the residues in the S2 subsite of HIV-1 protease. The syntheses of the ligands were carried out using the [5+2]-cycloaddition as the key step. Several inhibitors exhibited potent enzyme inhibitory activity. High resolution room-temperature X-ray structures of inhibitor-bound HIV-1 protease were determined. These structures provided important molecular insights for further design and optimization of inhibitor potency.

60 APPLIED LIFE SCIENCES↗

A novel approach for critical heat flux enhancement during severe accident mitigation with removal of radioactive materials from the coolant

In this paper, a new system, which consists of mature and proven technologies, is suggested for simultaneous objectives in nuclear power plants: CHF enhancement and effective decontamination. It consists of multifunctional magnetic nanoparticles and a collector part. CHF enhancement for severe accident mitigation strategies like IVR-ERVC and core catcher is expected along with an efficient decontamination process of target radioactive nuclides, and through the collector part, where external magnetic fields are applied, working fluid can be effectively purified. The multifunctional magnetic nanoparticle possesses potentials to severe accident scenarios based on its distinct characteristics. Also, a nanofluid system is strongly affected by environments and state of the immersed particles; the CHF enhancement can be stably achieved in real applications with proper consideration and optimization.

Kam, Dong Hoon↗

Comprehensive Efficiency Analysis of Current Source Inverter Based SPM Machine Drive System for Traction Applications

A current-source inverter (CSI) has the natural capability of boosting the output voltage which is a notable advantage over voltage source inverter (VSI) in traction drive applications. This paper investigates the voltage boosting feature of the CSI to improve the overall efficiency of the CSI-based surface permanent magnet (SPM) machine drive system in the constant power region. The effects of the boost function on the total system losses, including the machine copper loss, core loss, and magnet loss, as well as the device conduction and switching loss in the CSI and dc/dc converter, are described using analytical models. The operating characteristics of the machine and CSI are validated by 2-D finite-element analysis (FEA) and simulations. Based on the loss model, the effects of the modulation index on the overall drive system losses and power factor have been analyzed. A genetic algorithm has been used to optimize the CSI's boost ratio, demonstrating that the drive system efficiency can be increased by 1% to 2.5% along the constant-power regime envelope by using the boost function.

current source inverter, genetic algorithm, SPM ma↗