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At least 433 records · Page 24

Computer graphics for management: An abstract of capabilities and applications of the EIS system

The Executive Information Services (EIS) system, developed as a computer-based, time-sharing tool for making and implementing management decisions, and including computer graphics capabilities, was described. The following resources are available through the EIS languages: centralized corporate/gov't data base, customized and working data bases, report writing, general computational capability, specialized routines, modeling/programming capability, and graphics. Nearly all EIS graphs can be created by a single, on-line instruction. A large number of options are available, such as selection of graphic form, line control, shading, placement on the page, multiple images on a page, control of scaling and labeling, plotting of cum data sets, optical grid lines, and stack charts. The following are examples of areas in which the EIS system may be used: research, estimating services, planning, budgeting, and performance measurement, national computer hook-up negotiations.

Solem, B. J.↗

Flexibility and Performance of Parallel File Systems

As we gain experience with parallel file systems, it becomes increasingly clear that a single solution does not suit all applications. For example, it appears to be impossible to find a single appropriate interface, caching policy, file structure, or disk-management strategy. Furthermore, the proliferation of file-system interfaces and abstractions make applications difficult to port. We propose that the traditional functionality of parallel file systems be separated into two components: a fixed core that is standard on all platforms, encapsulating only primitive abstractions and interfaces, and a set of high-level libraries to provide a variety of abstractions and application-programmer interfaces (API's). We present our current and next-generation file systems as examples of this structure. Their features, such as a three-dimensional file structure, strided read and write interfaces, and I/O-node programs, are specifically designed with the flexibility and performance necessary to support a wide range of applications.

Kotz, David↗

Methods and Experiences for Developing Abstractions for Data-intensive, Scientific Applications

Developing software for scientific applications that require the integration of diverse types of computing, instruments, and data present challenges that are distinct from commercial software. These applications require scale, and the need to integrate various programming and computational models with evolving and heterogeneous infrastructure. Pervasive and effective abstractions for distributed infrastructures are thus critical; however, the process of developing abstractions for scientific applications and infrastructures is not well understood. While theory-based approaches for system development are suited for well-defined, closed environments, they have severe limitations for designing abstractions for scientific systems and applications. The design science research (DSR) method provides the basis for designing practical systems that can handle real-world complexities at all levels. In contrast to theory-centric approaches, DSR emphasizes both practical relevance and knowledge creation by building and rigorously evaluating all artifacts. In this work, we show how DSR provides a well-defined framework for developing abstractions and middleware systems for distributed systems. Specifically, we address the critical problem of distributed resource management on heterogeneous infrastructure over a dynamic range of scales, a challenge that currently limits many scientific applications. We use the pilot-abstraction, a widely used resource management abstraction for high-performance, high throughput, big data, and streaming applications, as a case study for evaluating the DSR activities. For this purpose, we analyze the research process and artifacts produced during the design and evaluation of the pilot-abstraction. We find DSR provides a concise framework for iteratively designing and evaluating systems. Finally, we capture our experiences and formulate different lessons learned.

97 MATHEMATICS AND COMPUTING↗

Outlook on texture evolution in additively manufactured stainless steels: Prospects for hydrogen embrittlement resistance, overview of mechanical, and solidification behavior

Abstract Realizing application specific manufacture with fusion-based additive manufacturing (F-BAM) processes requires understanding of the physical phenomena that drive evolution of microstructural attributes, such as texture. Current approaches for understanding texture evolution in F-BAM are majorly considerate of the phenomena occurring only during solidification. This hinders the comprehensive understanding and control of texture during F-BAM. In this perspective article, we discuss several physical phenomena occurring during and after solidification that can determine texture in F-BAM processed stainless steels (SS). A crystal plasticity-coupled hydrogen adsorption-diffusion modeling framework is also leveraged to demonstrate the prospects of grain boundary engineering with F-BAM for enhanced hydrogen embrittlement resistance of SS. Implications of varying thermokinetics in F-BAM for solidification behavior of SS are discussed. Additionally, microstructural attributes that are key to high temperature mechanical performance of SS are highlighted. Considerations as outlined in this perspective article will enable grain boundary engineering and application specific microstructural design of SS with F-BAM. Graphical abstract

36 MATERIALS SCIENCE↗

The Persistent Challenge of Data Locality in the Post-Exascale Era

The era of exascale computing, exemplified by systems like Frontier achieving exaflop-level performance, marks a milestone. However, the quest for sheer compute power leads to strong imbalance in system design. Hence, scaling advancements in memory, network bandwidth, and storage are also necessary and pose challenges, with a crucial need to address data locality issues. This article underscores the fundamental importance of data locality as a key abstraction for optimizing application performance. Despite notable software solutions, the growing complexity of parallelism and memory hierarchy demands performance-portable data locality solutions across diverse computing platforms. Additionally, the article revisits data locality aspects, covering hardware considerations, application perspectives, software stack abstractions, and tool support. It concludes with insights into data locality challenges and opportunities, emphasizing the ongoing significance of collaborative research for progress in this critical issue.

Unat, Didem [Koc University, Istanbul (Turkey)] (O↗

QuaSiMo: A composable library to program hybrid workflows for quantum simulation

Abstract A composable design scheme is presented for the development of hybrid quantum/classical algorithms and workflows for applications of quantum simulation. The proposed object‐oriented approach is based on constructing an expressive set of common data structures and methods that enables programming of a broad variety of complex hybrid quantum simulation applications. The abstract core of the scheme is distilled from the analysis of the current quantum simulation algorithms. Subsequently, it allows synthesis of new hybrid algorithms and workflows via the extension, specialisation, and dynamic customisation of the abstract core classes defined by the proposed design. The design scheme is implemented using the hardware‐agnostic programming language QCOR into the QuaSiMo library. To validate the implementation, the authors test and show its utility on commercial quantum processors from IBM and Rigetti, running some prototypical quantum simulations.

97 MATHEMATICS AND COMPUTING↗

Emerging Opportunities in Manufacturing Bulk Soft-Magnetic Alloys for Energy Applications: A Review

Abstract Soft-magnetic alloys exhibit exceptional functional properties that are beneficial for a variety of electromagnetic applications. These alloys are conventionally manufactured into sheet or bar forms using well-established ingot metallurgy practices that involve hot- and cold-working steps. However, recent developments in process metallurgy have unlocked opportunities to directly produce bulk soft-magnetic alloys with improved, and often tailorable, structure–property relationships that are unachievable conventionally. The emergence of unconventional manufacturing routes for soft-magnetic alloys is largely motivated by the need to improve the energy efficiency of electromagnetic devices. In this review, literature that details emerging manufacturing approaches for soft-magnetic alloys is overviewed. This review covers (1) severe plastic deformation, (2) recent advances in melt spinning, (3) powder-based methods, and (4) additive manufacturing. These methods are discussed in comparison with conventional rolling and bar processing. Perspectives and recommended future research directions are also discussed.

36 MATERIALS SCIENCE↗

Improved Verification and Validation Testing and Tools including Nuclear Criticality Safety Applications with the MCNP6.3® Code [Abstract]

A new Python-based framework has been developed to enable a more consistent layout with automatable setup, execution, and documentation of all verification and validation (V&V) test suites previously established for use with the MCNP code. In this paper, the new general framework for the V&V test suites is discussed, including information on all of the current capabilities and plans for future capabilities. For nuclear criticality safety applications, the existing V&V benchmark problems within the criticality, extended criticality, and analytic k-effective test suites have been ported into this new framework. In addition, the status and updates to the Rossi-alpha and subcritical multiplicationtest suites will be discussed. Some V&V results exercising new MCNP6.3 capabilities will be demonstrated.

97 MATHEMATICS AND COMPUTING↗

Design for dependability: A simulation-based approach

This research addresses issues in simulation-based system level dependability analysis of fault-tolerant computer systems. The issues and difficulties of providing a general simulation-based approach for system level analysis are discussed and a methodology that address and tackle these issues is presented. The proposed methodology is designed to permit the study of a wide variety of architectures under various fault conditions. It permits detailed functional modeling of architectural features such as sparing policies, repair schemes, routing algorithms as well as other fault-tolerant mechanisms, and it allows the execution of actual application software. One key benefit of this approach is that the behavior of a system under faults does not have to be pre-defined as it is normally done. Instead, a system can be simulated in detail and injected with faults to determine its failure modes. The thesis describes how object-oriented design is used to incorporate this methodology into a general purpose design and fault injection package called DEPEND. A software model is presented that uses abstractions of application programs to study the behavior and effect of software on hardware faults in the early design stage when actual code is not available. Finally, an acceleration technique that combines hierarchical simulation, time acceleration algorithms and hybrid simulation to reduce simulation time is introduced.

Goswami, Kumar K.↗

Unveiling the mechanism of remote epitaxy of crystalline semiconductors on 2D materials-coated substrates

Abstract Remote epitaxy has opened novel opportunities for advanced manufacturing and heterogeneous integration of two-dimensional (2D) materials and conventional (3D) materials. The lattice transparency as the fundamental principle of remote epitaxy has been studied and challenged by recent observations defying the concept. Understanding remote epitaxy requires an integrated approach of theoretical modeling and experimental validation at multi-scales because the phenomenon includes remote interactions of atoms across an atomically thin material and a few van der Waals gaps. The roles of atomically thin 2D material for the nucleation and growth of a 3D material have not been integrated into a framework of remote epitaxy research. Here, we summarize studies of remote epitaxy mechanisms with a comparison to other epitaxy techniques. In the end, we suggest the crucial topics of remote epitaxy research for basic science and applications. Graphical Abstract

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Modulating ion-binding at macromolecular interfaces during (bio)mineralization: A snapshot review for calcium carbonate and calcium phosphate systems

Abstract Local environments have strict influence over (bio)mineralization in calcifying systems. This snapshot review discusses recent insights into the roles of Ca 2+ -macromolecule interactions on the nucleation of calcium carbonate and calcium phosphate minerals. Experimental findings combined with simulations/modeling are providing breakthrough information and raising important questions for future studies. The emerging picture is that both nucleation and growth are driven by local ordering of ions and water about the macromolecule interface, rather than broader properties or molecular class. Tuning macromolecular properties at the atomic scale thus provides opportunities for highly specific controls on mineralization; however, many limitations and challenges remain. We highlight studies employing in-situ atomic force microscopy (AFM) and transmission electron microscopy (TEM) to observe crystallization processes on or near macromolecular substrates. As the distribution and ability of these techniques increases, fundamental studies integrating experimental and computational methods will be crucial to inform a broad range of applications. Graphical abstract

Knight, Brenna M. (ORCID:0000000244000067)↗

A model-independent data assimilation (MIDA) module and its applications in ecology

Abstract. Models are an important tool to predict Earth system dynamics. An accurate prediction of future states of ecosystems depends on not only model structures but also parameterizations. Model parameters can be constrained by data assimilation. However, applications of data assimilation to ecology are restricted by highly technical requirements such as model-dependent coding. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module. MIDA works in three steps including data preparation, execution of data assimilation, and visualization. The first step prepares prior ranges of parameter values, a defined number of iterations, and directory paths to access files of observations and models. The execution step calibrates parameter values to best fit the observations and estimates the parameter posterior distributions. The final step automatically visualizes the calibration performance and posterior distributions. MIDA is model independent, and modelers can use MIDA for an accurate and efficient data assimilation in a simple and interactive way without modification of their original models. We applied MIDA to four types of ecological models: the data assimilation linked ecosystem carbon (DALEC) model, a surrogate-based energy exascale earth system model: the land component (ELM), nine phenological models and a stand-alone biome ecological strategy simulator (BiomeE). The applications indicate that MIDA can effectively solve data assimilation problems for different ecological models. Additionally, the easy implementation and model-independent feature of MIDA breaks the technical barrier of applications of data–model fusion in ecology. MIDA facilitates the assimilation of various observations into models for uncertainty reduction in ecological modeling and forecasting.

58 GEOSCIENCES↗

3D printing of ceramics: Advantages, challenges, applications, and perspectives

Abstract 3D printing (3DP) technologies have transformed the processing of advanced ceramics for small‐scale and custom designs during the past three decades. Simple and complex parts are designed and manufactured using 3DP technologies for structural, piezoelectric, and biomedical applications. Manufacturing simple or complex geometries or one‐of‐a‐kind components without part‐specific tooling saves significant time and creates new applications for advanced ceramic materials. Although development and innovations in 3DP of ceramics are far behind compared with metals or polymers, with the availability of different commercial machines in recent years for 3DP of ceramics, exponential growth is expected in this field in the coming decade. This article details various 3DP technologies for advanced ceramic materials, their advantages and challenges for manufacturing parts for various applications, and perspectives on future directions. We envision this work will be helpful to advanced ceramic researchers in industry and academia who are using different 3DP processes in the coming days.

36 MATERIALS SCIENCE↗

Tuning Phonon Energies in Lanthanide‐doped Potassium Lead Halide Nanocrystals for Enhanced Nonlinearity and Upconversion

Abstract Optical applications of lanthanide‐doped nanoparticles require materials with low phonon energies to minimize nonradiative relaxation and promote nonlinear processes like upconversion. Heavy halide hosts offer low phonon energies but are challenging to synthesize as nanocrystals. Here, we demonstrate the size‐controlled synthesis of low‐phonon‐energy KPb 2 X 5 (X=Cl, Br) nanoparticles and the ability to tune nanocrystal phonon energies as low as 128 cm −1 . KPb 2 Cl 5 nanoparticles are moisture resistant and can be efficiently doped with lighter lanthanides. The low phonon energies of KPb 2 X 5 nanoparticles promote upconversion luminescence from higher lanthanide excited states and enable highly nonlinear, avalanche‐like emission from KPb 2 Cl 5 : Nd 3+ nanoparticles. The realization of nanoparticles with tunable, ultra‐low phonon energies facilitates the discovery of nanomaterials with phonon‐dependent properties, precisely engineered for applications in nanoscale imaging, sensing, luminescence thermometry and energy conversion.

Zhang, Zhuolei↗

Chemical recycling of polymer composites induced by selective variable frequency microwave heating

Abstract The application of variable frequency microwave (VFM) heating to achieve rapid thermal depolymerization of polymer composites is reported for the first time. The thermal and chemical influence of composite additives on polymer decomposition has been studied for a set of chemically recyclable polymers, including polyphthalaldehyde, polypropylene carbonate, two polyhydroxyalkanoates, and nylon 6. Carbon‐based additives, specifically nanocarbon particles, were used as effective microwave absorbers to controllably degrade the surrounding polymer matrix into valuable, monomeric compounds. Depolymerization and byproduct confirmation were quantified by gel permeation chromatography and nuclear magnetic resonance spectroscopy. Synergistic effects can be leveraged from pre‐treating composite samples to further reduce the total microwave energy required to depolymerize composite samples. This study establishes the use of VFM heating for chemical recycling of polymer composites that can be leveraged toward a plastic circular economy.

Polymer Science↗

Exposure History and its Effect Towards Stabilizing Li Exchange Across Disordered Rock Salt Interfaces

Abstract The application of lithium rich disordered rock salts (DRX) as cathode materials has greatly expanded the materials space for high energy density cathodes. These materials are able to consistently achieve capacities higher than via a complex percolation based intercalation mechanism. Most current DRX materials face significant capacity fade when cycled over an extended period. One of the factors responsible for this could be deleterious side effect of interface reactions between the electrode and electrolyte at high voltage. We aim to focus on one aspect of this interaction, i.e the effect of exposure to electrolyte on the surface and its effect on the electrochemical properties of (LMNOF) powder. LMNOF was systematically treated in an electrolyte solution for varying periods of time at an elevated temperature. Treated samples exhibit surface layer modification (removal of F rich surface layer), leading to a 10 % improvement in the capacity retention behavior of LMNOF. Surface and bulk based measurements indicate an increase in disorder and gradual removal of F and Li. All of these processes mimic an aging process similar to cycling. This a priori formed interface allows for increased stability with respect to retention of capacity and oxygen loss.

Satish, Rohit↗

Distributed deep reinforcement learning for simulation control

Abstract Several applications in the scientific simulation of physical systems can be formulated as control/optimization problems. The computational models for such systems generally contain hyperparameters, which control solution fidelity and computational expense. The tuning of these parameters is non-trivial and the general approach is to manually ‘spot-check’ for good combinations. This is because optimal hyperparameter configuration search becomes intractable when the parameter space is large and when they may vary dynamically. To address this issue, we present a framework based on deep reinforcement learning (RL) to train a deep neural network agent that controls a model solve by varying parameters dynamically. First, we validate our RL framework for the problem of controlling chaos in chaotic systems by dynamically changing the parameters of the system. Subsequently, we illustrate the capabilities of our framework for accelerating the convergence of a steady-state computational fluid dynamics solver by automatically adjusting the relaxation factors of the discretized Navier–Stokes equations during run-time. The results indicate that the run-time control of the relaxation factors by the learned policy leads to a significant reduction in the number of iterations for convergence compared to the random selection of the relaxation factors. Our results point to potential benefits for learning adaptive hyperparameter learning strategies across different geometries and boundary conditions with implications for reduced computational campaign expenses 4 4 Data and codes available at https://github.com/Romit-Maulik/PAR-RL . .

42 ENGINEERING↗