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At least 775 records · Page 43

Mapping a battlefield simulation onto message-passing parallel architectures

Perhaps the most critical problem in distributed simulation is that of mapping: without an effective mapping of workload to processors the speedup potential of parallel processing cannot be realized. Mapping a simulation onto a message-passing architecture is especially difficult when the computational workload dynamically changes as a function of time and space; this is exactly the situation faced by battlefield simulations. This paper studies an approach where the simulated battlefield domain is first partitioned into many regions of equal size; typically there are more regions than processors. The regions are then assigned to processors; a processor is responsible for performing all simulation activity associated with the regions. The assignment algorithm is quite simple and attempts to balance load by exploiting locality of workload intensity. The performance of this technique is studied on a simple battlefield simulation implemented on the Flex/32 multiprocessor. Measurements show that the proposed method achieves reasonable processor efficiencies. Furthermore, the method shows promise for use in dynamic remapping of the simulation.

Nicol, David M.↗

Illitization in the Mt. Simon Sandstone, Illinois Basin, USA: Implications for carbon dioxide storage

Clay mineral cementation is one of the most important controls on sandstone reservoir properties. Here, in this paper, the diagenetic history of the Mt. Simon reservoir complex is studied to reveal the origin, timing, and controls of illitization. Samples of sandstone and shale from Mt. Simon reservoir complex were acquired from the Illinois Basin–Decatur Project (IBDP), a CO 2 storage demonstration project in the central Illinois Basin. Petrographic, SEM, TEM, XRD analyses and K/Ar age dating were completed to identify the major detrital and diagenetic components of the samples and reveal illite to be the major clay component in all samples. Illitic clay coatings in the lower Mt. Simon reservoir are identified as a major control on reservoir properties by inhibiting major precipitation of authigenic quartz during illitization, resulting in highly permeable sandstone, essential for CO 2 storage. The coating box-work morphology and mineralogy are indicative of a detrital smectite origin with subsequent illite growth associated with feldspar dissolution and kaolinite alteration. The mineralogy of bulk material and separate grain size fractions (2–0.6 μm; 0.6–0.2 μm; < 0.2 μm) with illite polytypes 2M 1 , 1M, and 1M d were quantified and age dated via 40 K- 40 Ar methods. The shales or reservoir seals contain the highest proportions of detrital illite with illite in the lower Mt. Simon Sandstone reservoir identified as solely diagenetic. Two major events of illitization are identified throughout the Mt. Simon with more porous reservoir rock exhibiting the older event from approximately 360 to 315 Ma and tighter sandstone units with reservoir properties too low to be considered reservoir exhibiting illite dates from 250 to 220 Ma. This partitioning of illitization is attributed to varied mineralogy controlled by depositional changes and evolution of the greater basin.

58 GEOSCIENCES↗

PubChemLite Plus Collision Cross Section (CCS) Values for Enhanced Interpretation of Nontarget Environmental Data

Finding relevant chemicals in the vast (known) chemical space is a major challenge for environmental and exposomics studies leveraging nontarget high resolution mass spectrometry (NT-HRMS) methods. Chemical databases now contain hundreds of millions of chemicals, yet many are not relevant. This article details an extensive collaborative, open science effort to provide a dynamic collection of chemicals for environmental, metabolomics, and exposomics research, along with supporting information about their relevance to assist researchers in the interpretation of candidate hits. The PubChemLite for Exposomics collection is compiled from ten annotation categories within PubChem, enhanced with patent, literature and annotation counts, predicted partition coefficient (logP) values, as well as predicted collision cross section (CCS) values using CCSbase. Monthly versions are archived on Zenodo under a CC-BY license, supporting reproducible research, and a new interface has been developed, including historical trends of patent and literature data, for researchers to browse the collection. This article details how PubChemLite can support researchers in environmental and exposomics studies, describes efforts to increase the availability of experimental CCS values, and explores known limitations and potential for future developments. The data and code behind these efforts are openly available.

PubChem↗

A Principled Framework to Assess the Information-Theoretic Fitness of Brain Functional Sub-Circuits

In systems and network neuroscience, many common practices in brain connectomic analysis are often not properly scrutinized. One such practice is mapping a predetermined set of sub-circuits, like functional networks (FNs), onto subjects’ functional connectomes (FCs) without adequately assessing the information-theoretic appropriateness of the partition. Another practice that goes unchallenged is thresholding weighted FCs to remove spurious connections without justifying the chosen threshold. This paper leverages recent theoretical advances in Stochastic Block Models (SBMs) to formally define and quantify the information-theoretic fitness (e.g., prominence) of a predetermined set of FNs when mapped to individual FCs under different fMRI task conditions. Our framework allows for evaluating any combination of FC granularity, FN partition, and thresholding strategy, thereby optimizing these choices to preserve the important topological features of the human brain connectomes. By applying to the Human Connectome Project with Schaefer parcellations at multiple levels of granularity, the framework showed that the common thresholding value of 0.25 was indeed information-theoretically valid for group-average FCs, despite its previous lack of justification. Our results pave the way for the proper use of FNs and thresholding methods, and provide insights for future research in individualized parcellations.

Duong-Tran, Duy (ORCID:0009000944967575)↗

Hierarchial implicit dynamic least-square solution algorithm

This paper develops an implicit type transient solution strategy which possesses hierarchial levels of application. In particular, due to the manner of formulation, stiffness updating, assembly inversion, solution constraint, as well as iteration are all performed at a localized level. The level of iterative calculations depends on the type of hierarchial partitioning employed, namely degree of freedom, nodal, elemental, material/nonlinear group, substructural, and so on. Since the iterative solution process and application of constraints are applied at a local level, the resulting so-called hierarchial implicit solution algorithm possesses very stable and efficient numerical properties and is highly storage efficient. To demonstrate the scheme, the results of several benchmark examples are presented. These enable comparisons with the Newton-Raphson solved implicit transient solution method. Overall the comparisons illustrate the superior stability and efficiency of the hierarchial scheme.

Padovan, J.↗

Short-Term Retrospective Land Data Assimilation Schemes

Subsurface moisture and temperature and snow/ice stores exhibit persistence on various time scales that has important implications for the extended prediction of climatic and hydrologic extremes. Hence, to improve their specification of the land surface, many numerical weather prediction (NWP) centers have incorporated complex land surface schemes in their forecast models. However, because land storages are integrated states, errors in NWP forcing accumulates in these stores, which leads to incorrect surface water and energy partitioning. This has motivated the development of Land Data Assimilation Schemes (LDAS) that can be used to constrain NWP surface storages. An LDAS is an uncoupled land surface scheme that is forced primarily by observations, and is therefore less affected by NWP forcing biases. The implementation of an LDAS also provides the opportunity to correct the model's trajectory using remotely-sensed observations of soil temperature, soil moisture, and snow using data assimilation methods. The inclusion of data assimilation in LDAS will greatly increase its predictive capacity, as well as provide high-quality land surface assimilated data.

Houser, P. R.↗

Repartitioning the Hamiltonian in many-body second-order Brillouin–Wigner perturbation theory: Uncovering new size-consistent models

Second-order Møller-Plesset perturbation theory is well-known as a computationally inexpensive approach to the electron correlation problem that is size-consistent with a size-consistent reference but fails to be regular. On the other hand, the less well-known many-body version of Brillouin-Wigner perturbation theory has the reverse properties: it is regular but fails to be size-consistent when used with the standard MP partitioning. Consequently, its widespread use remains limited. In this work, we analyze the ways in which it is possible to use alternative non-MP partitions of the Hamiltonian to yield variants of BW2 that are size-consistent as well as regular. We show that there is a vast space of such BW2 theories and also show that it is possible to define a repartitioned BW2 theory from the ground state density alone, which regenerates the exact correlation energy. We also provide a general recipe for deriving regular, size-consistent, and size-extensive partitions from physically meaningful components, and we apply the result to small model systems. The scope of these results appears to further set the stage for a revival of BW2 in quantum chemistry.

Ab initio perturbation↗

UPC++ v1.0 Programmer’s Guide, Revision 2020.10.0

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.

97 MATHEMATICS AND COMPUTING↗

UPC++ v1.0 Programmer’s Guide, Revision 2020.3.0

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.

97 MATHEMATICS AND COMPUTING↗

Siderophile Element Profile Measurements in Iron Meteorites Using Laser Ablation ICP-MS

Understanding the behaviour of siderophile elements during cooling of iron meteorites can lead to insight into the general thermal histories of the meteorites as well as their respective parent bodies. Traditionally trace element analyses in meteorites have been done using techniques that only measure the average concentration in each phase. With these methods, all of the spatial information with respect to the distribution of an element within one phase is lost. Measuring concentration profiles of trace elements in meteorites is now possible, with the advent of high-resolution analytical techniques such as laser ablation, inductively coupled plasma mass spectrometry (LA-ICP-MS) with spatial resolution <20 microns. [e.g. 1,2] and secondary ion mass spectrometry [3]. These profiles can give more insight into both the partitioning and diffusive behavior of siderophile elements in metal systems relevant to iron meteorites, as well as parent body cooling rates.

Watson, H. C.↗

Os isotopes in SNC meteorites and their implications to the early evolution of Mars and Earth

A new development on the measurement of the Os isotopic composition by mass spectrometry using negative ions opened a new field of applications. The Re-Os systematic provides time information on the differentiation of the nobel metals. The nobel metals are strongly partitioned into metal and sulphide phases, but also the generation of silicate melts might fractionate the Re-Os system. Compared to the other isotopic systems which are mainly dating the fractionation of the alkalis and alkali-earth elements, the Re-Os system is expected to disclose entirely new information about the geochemistry. Especially the differentiation and early evolution of the planets such as the formation of the core will be elucidated with this method.

Jagoutz, E.↗

Reliability Modeling of Microelectromechanical Systems Using Neural Networks

Microelectromechanical systems (MEMS) are a broad and rapidly expanding field that is currently receiving a great deal of attention because of the potential to significantly improve the ability to sense, analyze, and control a variety of processes, such as heating and ventilation systems, automobiles, medicine, aeronautical flight, military surveillance, weather forecasting, and space exploration. MEMS are very small and are a blend of electrical and mechanical components, with electrical and mechanical systems on one chip. This research establishes reliability estimation and prediction for MEMS devices at the conceptual design phase using neural networks. At the conceptual design phase, before devices are built and tested, traditional methods of quantifying reliability are inadequate because the device is not in existence and cannot be tested to establish the reliability distributions. A novel approach using neural networks is created to predict the overall reliability of a MEMS device based on its components and each component's attributes. The methodology begins with collecting attribute data (fabrication process, physical specifications, operating environment, property characteristics, packaging, etc.) and reliability data for many types of microengines. The data are partitioned into training data (the majority) and validation data (the remainder). A neural network is applied to the training data (both attribute and reliability); the attributes become the system inputs and reliability data (cycles to failure), the system output. After the neural network is trained with sufficient data. the validation data are used to verify the neural networks provided accurate reliability estimates. Now, the reliability of a new proposed MEMS device can be estimated by using the appropriate trained neural networks developed in this work.

Perera. J. Sebastian↗

Definition of spectrally separable classes for soil survey research

A procedure is outlined for defining spectral classes such that the differences between classes can be quantified. It also facilitates determination of a number of classes such that the classes are spectrally discriminable. This is accomplished by partitioning the data into many classes and then combining similar spectral classes on the basis of appropriate criteria. Multispectral data were collected over a 12-mile flightline in White County, Indiana, in connection with the 1971 Corn Blight Watch Experiment. Data were collected in May by the University of Michigan airborne scanning spectrometer at an altitude of 5000 feet. Spectral maps resulting from the analysis were compared to existing soil surveys of the National Cooperative Soil Survey. The method should help determine the extent to which spectral properties of soil surfaces can be associated with morphologic and topographic differences of interest to soil surveyors engaged in operational soil mapping.

Cipra, J. E.↗

Effects of partitioning and scheduling sparse matrix factorization on communication and load balance

A block based, automatic partitioning and scheduling methodology is presented for sparse matrix factorization on distributed memory systems. Using experimental results, this technique is analyzed for communication and load imbalance overhead. To study the performance effects, these overheads were compared with those obtained from a straightforward 'wrap mapped' column assignment scheme. All experimental results were obtained using test sparse matrices from the Harwell-Boeing data set. The results show that there is a communication and load balance tradeoff. The block based method results in lower communication cost whereas the wrap mapped scheme gives better load balance.

Venugopal, Sesh↗

Quantify Contaminant Partitioning in Advanced Chlorination Process

Chlorination of the zirconium in spent fuel cladding has been identified as a significant means of Zr recovery and purification, enabling a 25% (wt.) or greater reduction in waste requiring geologic disposition. Several chlorinating agents have been identified over the last few years, including gases and liquids. In particular, the interactions of sulfur-chloride solvents with zirconium may allow the separation of zirconium from uranium with the selective formation of ZrCl 4 . This report reviews what is known about reactions between chlorinating agents, uranium metal and oxide, Zircaloy and its alloying elements, and fission plus activation products. Plans for testing the feasibility of applying advanced chlorination methods developed for zirconium recycling to the front end of the recycling of spent nuclear fuel are also included.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Toward computing bounds for Ramsey numbers using quantum annealing

Quantum annealing is a powerful tool for solving and approximating combinatorial optimization problems, such as graph partitioning, community detection, centrality, routing problems, and more. In this paper we explore the use of quantum annealing as a tool for use in exploring combinatorial mathematics research problems. We consider the monochromatic triangle problem and the Ramsey number problem, both examples of graph coloring. Conversion to quadratic unconstrained binary optimization (QUBO) form is required to run on quantum hardware. While the monochromatic triangle problem is quadratic by nature, the Ramsey number problem requires the use of order reduction methods for a quadratic formulation. The goal is to provide a method for producing special colorings of graphs which if successful would provide lower bounds for certain Ramsey numbers. We discuss implementations, limitations, and results when running on the D-Wave Advantage quantum annealer.

97 MATHEMATICS AND COMPUTING↗

Time-dependent-bases with local CUR decomposition method for accelerating turbulent combustion simulations

Here, this study presents a novel reduced-order modeling framework, Time-Dependent Bases with Local CUR decomposition (TDB-L-CUR), designed to efficiently and accurately approximate the species transport equations in reacting flow simulations. The method extends the existing TDB-CUR approach for chemically reacting flows (Jung et al. Comput. Methods Appl. Mech. Engrg. 437 (2025) 117758), which leverages matrix decomposition techniques to form a global-in-space, time-dependent low-dimensional manifold. While TDB-CUR performs well in homogeneous systems, it may be less well-suited to spatially heterogeneous systems such as turbulent flames, where higher-rank approximations are typically required. The proposed TDB-L-CUR framework introduces two methodological extensions to the baseline approach. First, it applies unsupervised clustering to partition the physical domain into distinct regions, enabling spatially localized manifold construction, thereby reducing the rank required for the reduced-order representation. Second, it incorporates a computational singular perturbation (CSP)-based scheme for identifying and penalizing fast species, allowing for spatio-temporally adaptive mitigation of chemical stiffness. The proposed framework is validated on a hierarchy of test cases, including a one-dimensional premixed flame, a two-dimensional nonpremixed ignition case with vortex interaction, and a three-dimensional turbulent premixed flame. TDB-L-CUR significantly improves accuracy over TDB-CUR while further reducing computational cost. The fully on-the-fly formulation of TDB-L-CUR (i.e., requiring no offline training or prior knowledge) makes it a robust and scalable tool for reduced-order modeling of reactive flows.

Local manifold↗

Method for Balancing Detector Output to a Desired Level of Balance at a Frequency

A multi-gas sensor is provided which modulates a polarized light beam over a broadband of wavelengths between two alternating orthogonal polarization components. The two orthogonal polarization components of the polarization modulated beam are directed along two distinct optical paths. At least one optical path contains one or more spectral discrimination elements, with each spectral discrimination element having spectral absorption features of one or more gases of interest being measured. The two optical paths then intersect, and one orthogonal component of the intersected components is transmitted and the other orthogonal component is reflected. The combined polarization modulated beam is partitioned into one or more smaller spectral regions of interest where one or more gases of interest has an absorption band. The difference in intensity between the two orthogonal polarization components is then determined in each partitioned spectral region of interest as an indication of the spectral emission/absorption of the light beam by the gases of interest in the measurement path. The spectral emission/absorption is indicative of the concentration of the one or more gases of interest in the measurement path. More specifically, one embodiment of the present invention is a gas filter correlation radiometer which comprises a polarizer, a polarization modulator, a polarization beam splitter, a beam combiner, wavelength partitioning element, and detection element. The gases of interest are measured simultaneously and, further, can be measured independently or non-independently. Furthermore, optical or electronic element are provided to balance optical intensities between the two optical paths.

Sachse, Glenn W.↗