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At least 271 records · Page 15

A survey of nonlinear robust optimization

Robust optimization (RO) has attracted great attention from the optimization community over the past decade. RO is dedicated to solving optimization problems subject to uncertainty: design constraints must be satisfied for all the values of the uncertain parameters within a given uncertainty set. Uncertainty sets may be modeled as deterministic sets (boxes, polyhedra, ellipsoids), in which case the RO problem may be reformulated via worst-case analysis, or as families of distributions. The challenge of RO is to reformulate or approximate robust constraints so that the uncertain optimization problem is transformed into a tractable deterministic optimization problem. Most reformulation methods assume linearity of the robust constraints or uncertainty sets of favorable shape, which represents only a fraction of real-world applications. This survey addresses nonlinear RO and includes problem formulations and applications, solution approaches, and available software with code samples.

97 MATHEMATICS AND COMPUTING↗

Wavelet flow for extragalactic foreground simulations

Extragalactic foregrounds in cosmic microwave background (CMB) observations are both a source of cosmological and astrophysical information and a nuisance to the CMB. Effective field-level modeling that captures their non-Gaussian statistical distributions is increasingly important for optimal information extraction, particularly given the low-noise observations from current and upcoming experiments. Here, we explore the use of Wavelet Flow (WF) models to tackle the novel task of modeling the field-level probability distributions of multi-component CMB secondaries and foregrounds. Specifically, we jointly train correlated CMB lensing convergence (κ) and cosmic infrared background (CIB) maps with a WF model and obtain a network that statistically recovers the input to high accuracy — the trained network generates samples of κ and CIB fields whose average power spectra are within a few percent of the inputs across all scales, and whose Minkowski functionals are similarly accurate compared to the inputs. Leveraging the multiscale architecture of these models, we fine-tune both the model parameters and the priors at each scale independently, optimizing performance across different resolutions. These results demonstrate that WF models can accurately simulate correlated components of CMB secondaries, supporting improved analysis of cosmological data. Our code and trained models can be found on this GitHub repo.

cosmological simulations↗

Simulations of future particle accelerators: issues and mitigations

The ever increasing demands placed upon machine performance have resulted in the need for more comprehensive particle accelerator modeling. Computer simulations are key to the success of particle accelerators. Many aspects of particle accelerators rely on computer modeling at some point, sometimes requiring complex simulation tools and massively parallel supercomputing. Examples include the modeling of beams at extreme intensities and densities (toward the quantum degeneracy limit), and with ultra-fine control (down to the level of individual particles). In the future, adaptively tuned models might also be relied upon to provide beam measurements beyond the resolution of existing diagnostics. Much time and effort has been put into creating accelerator software tools, some of which are highly successful. However, there are also shortcomings such as the general inability of existing software to be easily modified to meet changing simulation needs. In this paper possible mitigating strategies are discussed for issues faced by the accelerator community as it endeavors to produce better and more comprehensive modeling tools. This includes lack of coordination between code developers, lack of standards to make codes portable and/or reusable, lack of documentation, among others.

43 PARTICLE ACCELERATORS↗

Mycobacterium tuberculosis Phe-tRNA synthetase: structural insights into tRNA recognition and aminoacylation

Abstract Tuberculosis, caused by Mycobacterium tuberculosis, responsible for ∼1.5 million fatalities in 2018, is the deadliest infectious disease. Global spread of multidrug resistant strains is a public health threat, requiring new treatments. Aminoacyl-tRNA synthetases are plausible candidates as potential drug targets, because they play an essential role in translating the DNA code into protein sequence by attaching a specific amino acid to their cognate tRNAs. We report structures of M. tuberculosis Phe-tRNA synthetase complexed with an unmodified tRNAPhe transcript and either L-Phe or a nonhydrolyzable phenylalanine adenylate analog. High-resolution models reveal details of two modes of tRNA interaction with the enzyme: an initial recognition via indirect readout of anticodon stem-loop and aminoacylation ready state involving interactions of the 3′ end of tRNAPhe with the adenylate site. For the first time, we observe the protein gate controlling access to the active site and detailed geometry of the acyl donor and tRNA acceptor consistent with accepted mechanism. We biochemically validated the inhibitory potency of the adenylate analog and provide the most complete view of the Phe-tRNA synthetase/tRNAPhe system to date. The presented topography of amino adenylate-binding and editing sites at different stages of tRNA binding to the enzyme provide insights for the rational design of anti-tuberculosis drugs.

59 BASIC BIOLOGICAL SCIENCES↗

SALSA_python (SALSython) v1

SALSA_python (Semi-Analytical Leakage Solutions for Aquifers) is a software that computed semi-analytical solutions for hydraulic head and brine leakage in multilayered aquifer–aquitard systems with geologic pressure forcing. It can simulate brine leakage into aquifers in a multi-aquifer-aquitard system with multiple injection and leaky wells. This situation is encountered in underground CO2 storage wherein brine leakage from pressurized reservoirs into aquifers is of concern. SALSA_python calls the original SALSA[1] subroutines in python by using the salsa2.so library. This enables the incorporation and coupling of SALSA computations into existing python-based codes and tools. SALSA_python is available for Linux and Mac operating systems. [1] Cihan, A., Oldenburg, C. M., & Birkholzer, J. T. (2022). Leakage from coexisting geologic forcing and injection-induced pressurization: A semi-analytical solution for multilayered aquifers with multiple wells. Water Resources Research, 58, e2022WR032343.

Bhuvankar, Pramod↗

Advances in GDSA Framework Development and Process Model Integration

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and highlevel nuclear waste (HLW). A high priority for SFWST disposal R&D is to develop a disposal system modeling and analysis capability for evaluating disposal system performance for nuclear waste in geologic media. This report describes fiscal year (FY) 2020 advances of the Geologic Disposal Safety Assessment (GDSA) Framework and PFLOTRAN development groups of the SFWST Campaign. The common mission of these groups is to develop a geologic disposal system modeling capability for nuclear waste that can be used to probabilistically assess the performance of disposal options and generic sites. The capability is a framework called GDSA Framework that employs high-performance computing (HPC) capable codes PFLOTRAN and Dakota.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

L-BFGS Class Implementation in C++

This report presents a header-only C++ class implementation of the Limited-memory BroydenFletcher-Goldfarb-Shanno (L-BFGS) algorithm. The L-BFGS method is a general purpose quasi-Netwon optimization method that builds an approximation of the descent direction from consecutive iterate and gradient vectors. The limited-memory aspect stems from the replacement of the N × N approximation matrix of the original BFGS method with M vectors of length N. An example usage of the class is included along with the reference source code.

97 MATHEMATICS AND COMPUTING↗

Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials

Accurate molecular property predictions require 3D geometries, which are typically obtained using expensive methods such as density functional theory (DFT). Here, we attempt to obtain molecular geometries by relying solely on machine learning interatomic potential (MLIP) models. To this end, we first curate a large-scale molecular relaxation dataset comprising 3.5 million molecules and 300 million snapshots. Then MLIP pre-trained models are trained with supervised learning to predict energy and forces given 3D molecular structures. Once trained, we show that the pre-trained models can be used in different ways to obtain geometries either explicitly or implicitly. First, it can be used to obtain approximate low-energy 3D geometries via geometry optimization. While these geometries do not consistently reach DFT-level chemical accuracy or convergence, they can still improve downstream performance compared to non-relaxed structures. To mitigate potential biases and enhance downstream predictions, we introduce geometry fine-tuning based on the relaxed 3D geometries. Second, the pre-trained models can be directly fine-tuned for property prediction when ground truth 3D geometries are available. Our results demonstrate that MLIP pre-trained models trained on relaxation data can learn transferable molecular representations to improve downstream molecular property prediction and can provide practically valuable but approximate molecular geometries that benefit property predictions. Our code is publicly available at: https://github.com/divelab/AIRS/.

Fu, Cong [Texas A & M Univ., College Station, TX (↗

The Distant, Galaxy Cluster Environment of the Short GRB 161104A at $z\sim 0.8$ and a Comparison to the Short GRB Host Population

We present optical observations of the Swift short-duration gamma-ray burst (GRB) GRB 161104A and its host galaxy at z = 0.793 ± 0.003. We model the multiband photometry and spectroscopy with the stellar population inference code Prospector and explore the posterior using nested sampling. We find a mass-weighted age of $t_m = 2.12^{+0.23}_{-0.21}$ Gyr, stellar mass of log(M/M ⊙ ), metallicity of log(Z/Z ⊙ ), dust extinction of $A_V = 0.08^{+0.08}_{-0.05}$, and low star formation rate of 9.9 × 10 -2 M ⊙ yr -1 . These properties, along with a prominent 4000 Å break and optical absorption lines, classify this host as an early-type, quiescent galaxy. Using Dark Energy Survey galaxy catalogs, we demonstrate that the host of GRB 161104A resides on the outskirts of a galaxy cluster at z ≈ 0.8, situated ≈1 Mpc from the likely brightest cluster galaxy. We also present new modeling for 20 additional short GRB hosts (≈33% of which are early-type galaxies), finding population medians of and $t_m = 1.07^{+1.98}_{-0.67}$ Gyr (68% confidence). We further find that the host of GRB 161104A is more distant, less massive, and younger than the four other short GRB hosts known to be associated with galaxy clusters. Cluster short GRBs have faint afterglows, in the lower ≈11% (≈30%) of observed X-ray (optical) luminosities. We place a lower limit on the fraction of short GRBs in galaxy clusters versus those in the field of ≈5%–13%, consistent with the fraction of stellar mass of ≈10%–20% in galaxy clusters at redshifts 0.1 ≤ z ≤ 0.8. Future studies that take advantage of wider-field and deeper cluster surveys are needed to understand the true rate of short GRBs in clusters and their effect on heavy-element enrichment in the intracluster medium.

79 ASTRONOMY AND ASTROPHYSICS↗

Key Technical Issues for Greater-Than-Class-C (GTCC) Waste Disposal - 20164

Greater-than-Class C (GTCC) waste is low-level waste (LLW) that exceeds the Class C concentrations tabulated in Title 10, Code of Federal Regulations (CFR), Part 61. Disposal of GTCC waste in the near surface (i.e. upper 30 m of the earth's surface) is prohibited in the United States. Though GTCC waste disposal is generally prohibited, the Commission can approve disposal according to 10 CFR 61.55(a)(2)(iv) on a case-by-case basis. The waste classification tables, developed in the early 1980's, were based on model projections of dose to an inadvertent intruder in agricultural, construction, and discovery exposure scenarios. The assumptions and parameters used were documented in a series of public reports. Though different disposal facility designs and site conditions were considered, the waste classification tables were based on a disposal facility design located in a specific environment. The tables were based on shallow (i.e., top few meters) trench facility designs and did not consider deeper facilities. To determine the suitability of GTCC waste disposal in the near-surface, site-specific analyses must account for differences between GTCC waste and Class A, B, and C LLW (hereafter, traditional LLW). GTCC waste can have concentrations of radionuclides that are much higher than traditional LLW. Because of these higher concentrations, processes that are typically not significant for traditional LLW may be significant with respect to disposal of GTCC waste. These processes include, but are not limited to, heat generation, criticality, and radiolysis. The form of the waste as well as the barriers to release of the waste (e.g. waste package) could be substantially different than they are for traditional LLW. These barriers need to be considered when assessing the impacts of accidents during receipt and placement and in evaluating long-term performance. Some GTCC radioactivity is either embedded in stainless steel or contained in stainless steel barriers. Stainless steel can have very low corrosion rates under a variety of environmental conditions. Finally, and possibly most importantly, GTCC waste would likely need to be disposed deeper than traditional LLW to reduce the probability of disturbance. The waste classification table values of traditional LLW are based on an inadvertent intruder excavating into the waste and bringing some of the material to the land surface. If waste is deeper than approximately 5 m, the excavation scenario becomes very unlikely. Therefore, other intruder scenarios, such as drilling exposure scenarios, need to be evaluated. This paper summarizes key technical issues for the disposal of GTCC waste. Our previous study shows that certain GTCC waste may be suitable for near surface disposal whereas others may not. This study may support ongoing technical analyses assessing potential disposal of GTCC in a near surface disposal facility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Betelgeuse as a Merger of a Massive Star with a Companion

We investigate the merger between a 16M ⊙ star, on its way to becoming a red supergiant (RSG), and a 4M ⊙ main-sequence companion. Our study employs three-dimensional hydrodynamic simulations using the state-of-the-art adaptive mesh refinement code Octo-Tiger. The initially corotating binary undergoes interaction and mass transfer, resulting in the accumulation of mass around the companion and its subsequent loss through the second Lagrangian point (L2). The companion eventually plunges into the envelope of the primary, leading to its spin-up and subsequent merger with the helium core. We examine the internal structural properties of the post-merger star, as well as the merger environment and the outflow driven by the merger. Our findings reveal the ejection of approximately ∼0.6 M ⊙ of material in an asymmetric and somewhat bipolar outflow. We import the post-merger stellar structure into the MESA stellar evolution code to model its long-term nuclear evolution. In certain cases, the post-merger star exhibits persistent rapid equatorial surface rotation as it evolves in the H–R diagram toward the observed location of Betelgeuse. These cases demonstrate surface rotation velocities of a similar magnitude to those observed in Betelgeuse, along with a chemical composition resembling that of Betelgeuse. In other cases, efficient rotationally induced mixing leads to slower surface rotation. This pioneering study aims to model stellar mergers across critical timescales, encompassing dynamical, thermal, and nuclear evolutionary stages.

79 ASTRONOMY AND ASTROPHYSICS↗

Electric Readiness in Residential Energy Code: Technical Brief

This technical brief provides requirements for electric readiness that could be incorporated into model residential energy codes. It provides background on the basis and benefits of the provisions, and model code language that can be plugged into the IECC or adapted into other energy codes. This brief has been updated to reflect changes in the 2024 IECC.

2021 IECC↗

A discrete integral transform for rapid spectral synthesis

Accurate synthetic spectra that rely on large Line-By-Line (LBL)-databases are used in a wide range of applications such as high temperature combustion, atmospheric re-entry, planetary surveillance and laboratory plasmas. Conventionally synthetic spectra are calculated by computing a lineshape for every spectral line in the database and adding those together, which may take multiple hours for large databases. In this paper we propose a new approach for spectral synthesis based on an integral transform: the synthetic spectrum is calculated as the integral over the product of a Voigt profile and a newly proposed three-dimensional “lineshape distribution function”, which is a function of spectral position and Gaussian- & Lorentzian width coordinates. A fast discrete version of this transform based on the Fast Fourier Transform (FFT) is proposed, which improves performance compared to the conventional approach by several orders of magnitude while maintaining accuracy. Strategies that minimize the discretization error are discussed. A Python implementation of the method is compared against state-of-the-art spectral code RADIS, and is since adopted as RADIS's default synthesis method. The synthesis of a benchmark CO2 spectrum consisting of 1.8 M spectral lines and 200k spectral points took only 3.1 s using the proposed method (1011 lines × spectral points/s), a factor ~300 improvement over the state-of-the-art, with the relative improvement generally increasing for higher number of lines and/or number of spectral points. Finally, an experimental GPU-implementation of the method was also benchmarked, which demonstrated another 2~3 orders performance increase, achieving up to 5 ∙ 10 14 lines × spectral points/s.

42 ENGINEERING↗

Zero power experiment for molten salt reactor - code verification and validation request

Molten Salt Reactors (MSRs) are one of the six perspective Generation IV nuclear technologies that should fulfil sustainability, economics, safety, and proliferation resistance goals. In recent years these concepts have attracted increased interest in research as well as in industry. In the context of developing new, innovative technology, a zero-power experiment would be an ideal option for improving the understanding of MSR systems under low-risk and low-cost conditions. The given research was focused on cross-verification of the nuclear codes for MSR modelling and simulations as required for the development of the first design of a potential facility and a draft of an experimental programme. The analysis included the evaluation of lattice and Monte Carlo codes. The study showed that all considered nuclear tools were in good agreement with each other. Although this does not mean the results will match the real experimental data, which is essential for the regulatory approval of a novel technology. Currently, experimental data is almost absent for MSR technology. Hence, a zero power experiment is needed to assure we can rely on modelling and simulation studies for further development of MSR technology and deliver real-world experiments to support the licensing of future MSRs. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Electrostatic Relativistic Fluid Models of Electron Emission in a Warm Diode

A semi-analytic fluid model has been developed for characterizing relativistic electron emission across a warm diode gap. Here we demonstrate the use of this model in (i) verifying multi-fluid codes in modeling compressible relativistic electron flows (the EMPIRE-Fluid code is used as an example; see also Ref. 1), (ii) elucidating key physics mechanisms characterizing the influence of compressibility and relativistic injection speed of the electron flow, and (iii) characterizing the regimes over which a fluid model recovers physically reasonable solutions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Variations in lithium vapor cave performance predictions due to radial transport and recycling assumptions

The lithium vapor cave is a detached divertor design that uses a single private flux region baffle to contain a dense cloud of lithium vapor to dissipate heat flux. Plasma flows are created via fuel gas puffing in order to minimize lithium contamination of the main plasma. Significant modeling using the 2D edge code SOLPS-ITER has already been performed, predicting that sufficient target heat flux reductions (q$^{max}_{Target}$ MW m −2 ) with ( $n$ Li /$n$ e ) LCFS < 0.05 is possible in a case with 90 MW m −2 unmitigated heat flux in NSTX-U. Low heat flux and low upstream concentration was found with a variety of combinations of divertor geometries, target recycling coefficients, upstream plasma parameters, lithium evaporation locations and deuterium fueling locations, with variations in performance found for each design choice. However, the most universal uncertainty of SOLPS-ITER simulations has until now remained unaddressed systematically, namely the cross-field anomalous particle and heat diffusivities. This article aims to bound the uncertainty in lithium concentration prediction as a result of the assumed deuterium cross-field transport and recycling. For the simulations presented here, a factor of 2.1 increase in the upstream lithium density prediction across a factor of four decrease to the assumed deuterium radial particle diffusivity is found. This result is compared across different assumed deuterium recycling coefficients, known to reduce with lithium injection. Upstream lithium density is found to vary by a factor of 2.4 across a feasible range of recycling coefficients at similar $n$$^{OMP,sep}_{e}$.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗